Best SPSS Courses

Find the best online SPSS Courses for you. The courses are sorted based on popularity and user ratings. We do not allow paid placements in any of our rankings. We also have a separate page listing only the Free SPSS Courses.

SPSS For Research

SPSS data analysis made easy. Become an expert in advanced statistical analysis with SPSS.

Created by Bogdan Anastasiei - University Teacher and Consultant

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Students: 36135, Price: $49.99

Students: 36135, Price:  Paid

Become an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video!

Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis.

The good news – you don't need any previous experience with SPSS. If you know the very basic statistical concepts, that will do.

And you don't need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians – all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained.

Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it.

Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word.

For each statistical procedure I provide the following pieces of information:

  • a short, but comprehensive description (so you understand what that technique can do for you)
  • how to perform the procedure in SPSS (live)
  • how to interpret the main output, so you can check your hypotheses and find the answers you need for your research)

The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don't go far beyond the basics).

The first guides are absolutely free, so you can dive into the course right now, at no risk. And don't forget that you have 30 full days to evaluate it. If you are not happy, you get your money back.

So, what do you have to lose?

Advanced Data Science Techniques in SPSS

Hone your SPSS skills to perfection - grasp the most high level data analysis methods available in the SPSS program.

Created by Bogdan Anastasiei - University Teacher and Consultant

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Students: 25060, Price: $79.99

Students: 25060, Price:  Paid

Become a Top Performing Data Analyst – Take This Advanced Data Science Course in SPSS!

Within a few days only you can master some of the most complex data analysis techniques available in the SPSS program. Even if you are not a professional mathematician or statistician, you will understood these techniques perfectly and will be able to apply them in practical, real life situations.

These methods are used every day by data scientists and data miners to make accurate predictions using their raw data. If you want to be a high skilled analyst, you must know them!

Without further ado, let’s see what you are going to learn…

  • Stepwise regression analysis, a technique that helps you select the best subset of predictors for a regression analysis, when you have a big number of predictors. This way you can create regression models that are both parsimonious and effective.
  • Nonlinear regression analysis. After finishing this course, you will be able to fit any nonlinear regression model using SPSS.
  • K nearest neighbor, a very popular predictive technique used mostly for classification purposes. So you will learn how to predict the values of a categorical variable with this method.
  • Decision trees. We will approach both binary (CART) and non-binary (CHAID) trees. For each of these two types we will consider two cases: the case of response dependent variables (regression trees) and the case of categorical response variables (classification trees).
  • Neural networks. Artificial neural networks are hot now, since they are a suitable predictive tool in many situations. In SPSS we can train two types of neural network: the multilayer perceptron (MLP) and the radial basis function (RBF) network. We are going to study both of them in detail.

  • Two-step cluster analysis, an effective grouping procedure that allows us to identify homogeneous groups in our population. It is useful in very many fields like marketing research, medicine (gene research, for example), biology, computer science, social science etc.
  • Survival analysis. If you have to estimate one of the following: the probable time until a certain event happens, what percentage of your population will suffer the event or which particular circumstances influence the probability that the event happens, than you need to apply on of the survival analysis method studied here: Kaplan-Meier or Cox regression.

For each analysis technique, a short theoretical introduction is provided, in order to familiarize the reader with the fundamental notions and concepts related to that technique. Afterwards, the analysis is executed on a real-life data set and the output is thoroughly explained.

Moreover, for some techniques (KNN, decision trees, neural networks) you will also learn:

  • How to validate your model on an independent data set, using the validation set approach or the cross-validation
  • How to save the model and use it for make predictions on new data that may be available in the future.

Join right away and start building sophisticated, in-demand data analysis skills in SPSS!

 

 

Customer Analytics in SPSS

Identify your best customers and increase response rates, customer loyalty and profits

Created by Bogdan Anastasiei - University Teacher and Consultant

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Students: 22780, Price: $49.99

Students: 22780, Price:  Paid

Learn how to get insights from your customer data, understand your customers deeply and target the right customers with the right products!

The SPSS program offers a comprehensive customer analytics tool – the Direct Marketing module. With this tool you can conduct powerful analyses without being an expert in statistics and data analysis.

The everyday interactions with your customer generates a high amount of valuable data. The customer marketing analysis is the best solution to transform these data into real knowledge. The goal of this analysis is to get you a precise view of your customers, identify the most profitable groups of customers and send them the most appropriate marketing messages.

The Direct Marketing toolkit in SPSS includes six practical analysis procedures. Each of these procedures has its own section in this course.

  1. The RFM analysis allows you to classify your customers according to the recency, frequency, and monetary value of their purchases. You can pinpoint your most valuable customers (those who buy often and spend much money), as well as adapt your strategy for each RFM customers (e.g. encourage new customers to buy more, reward good customers with discounts and prizes, re-gain old customers that stopped buying from you etc.)
  2. The cluster analysis procedure helps you segment your customers or prospects using their most relevant demographic, economic or behavioral characteristics. In each cluster you will find customers that are similar with eah other and different to the others. You can combine this procedure with other analyses, to identify the segments with the highest RFM values, for example, or to estimate the buying probability in each segment.
  3. The customer profiling technique helps you detect the customer groups with the highest response rate, based on the results of previous campaign. This way you can know in advance which customers are more likely to respond to your future offers. In consequence, you can significantly improve the targeting of your future campaigns, reduce campaign costs and increase sales and ROI.
  4. Another procedure allows you to identify the responses to your campaign  by postal codes. This is extremely useful for direct mailing campaigns, because you can find out the geographical areas where most of your customers live. You can compare the response rate of each geographical zone to your target rate and decide where to send your future mailing packages so you can maximize your profits.
  5. The Direct Marketing module in SPSS also helps you estimate the probability of purchase for each contact in your list, using an advanced prediction analysis method (binomial regression). You can send your future messages only to the prospects who are most likely to buy from you and remove the inactive prospects from your list. Moreover, you can predict the probability of purchasing for new customers, those freshly added to your list.
  6. The Control Package Test method allows you to compare the effectiveness of two or more marketing campaigns. This is useful especially when you intend to test existing campaigns against new campaigns. The differences between the campaigns response rates are evaluated using the binomial test.

Most of the procedures above use sophisticated statistical analysis techniques to process your data. However, you don’t have to be a statistician in order to use them. You can get the results you need with a few clicks only, in a few seconds. This is what you will learn in this course.

Every procedure is explained live in SPSS, and the output is interpreted in detail. At the end of each section you can find a couple of practical exercises to strengthen your knowledge.    

Join this course today and you will be able to analyze your customer data using state-of-the-art predictive techniques and make informed decisions!

 

SPSS Masterclass: Learn SPSS From Scratch to Advanced

A complete step by step course to master IBM SPSS Statistics for doing advanced Research, Statistics & Data Analysis

Created by Scholarsight Learning - Courses in High Impact Research & Technology

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Students: 19678, Price: $89.99

Students: 19678, Price:  Paid

Data is the new frontier of 21st century. According to a Harvard Business Report (2012) data science is going to be the hottest job of 21st century and data analysts have a very bright career ahead. This course aims to equip learners with ability of independently carrying out in-depth data analysis with professional confidence and accuracy. It will specifically help those looking to derive business insights, understand consumer behaviour, develop objective plans for new ventures, brand study, or write a scholarly articles in high impact journals and develop high quality thesis/project work.

A good knowledge of quantitative data analysis is a sine qua none for progress in academic and corporate world. Keeping this in mind this course has been designed in such way that students, researchers, teachers and corporate professionals who want to equip themselves with sound skills of data analysis and wish to progress with this skill can learn it in in-depth and interesting manner using IBM SPSS Statistics.

Lesson Outcomes

On completion of this course you will develop an ability to independently analyze and treat data, plan and carry out new research work based on your research interest. The course encompasses most of the major type of research techniques employed in academic and professional research in most comprehensive, in-depth and stepwise manner.

Pedagogy

The focus of current training program will be to help participants learn statistical skills through exploring SPSS and its different options. The focus will be to develop practical skills of analyzing data, developing an independent capacity to accurately decide what statistical tests will be appropriate with a particular kind of research objective. The program will also cover how to write the obtained output from SPSS in APA format.

Pre-requisite

A love for data analysis and statistics, research aptitude and motivation to do great research work.

Statistics / Data Analysis in SPSS: Inferential Statistics

Increase Your Data Analytic Skills – Highly Valued And Sought After By Employers

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

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Students: 5376, Price: $94.99

Students: 5376, Price:  Paid

November, 2019. 

Join more than 1,000 students and get instant access to this best-selling content - enroll today!

Get marketable and highly sought after skills in this course that will substantially increase your knowledge of data analytics, with a focus in the area of significance testing, an important tool for A/B testing and product assessment.

Many tests covered, including three different t tests, two ANOVAs, post hoc tests, chi-square tests (great for A/B testing), correlation, and regression. Database management also covered!

Two in-depth examples provided of each test for additional practice.

This course is great for professionals, as it provides step by step instruction of tests with clear and accurate explanations. Get ahead of the competition and make these tests important parts of your data analytic toolkit!

Students will also have the tools needed to succeed in their statistics and experimental design courses.

Data Analytics is an rapidly growing area in high demand (e.g., McKinsey)

Statistics play a key role in the process of making sound business decisions that will generate higher profits. Without statistics, it's difficult to determine what your target audience wants and needs. 

  Inferential statistics, in particular, help you understand a population's needs better so that you can provide attractive products and services. 

  This course is designed for business professionals who want to know how to analyze data. You'll learn how to use IBM SPSS to draw accurate conclusions on your research and make decisions that will benefit your customers and your bottom line. 

  Use Tests in SPSS to Correctly Analyze Inferential Statistics 

  • Use the One Sample t Test to Draw Conclusions about a Population

  • Understand ANOVA and the Chi Square

  • Master Correlation and Regression

  • Learn Data Management Techniques

  Analyze Research Results Accurately to Make Better Business Decisions 

  With SPSS, you can analyze data to make the right business decisions for your customer base. And by understanding how to use inferential statistics, you can draw accurate conclusions about a large group of people, based on research conducted on a sample of that population. 

  This easy-to-follow course, which contains illustrative examples throughout, will show you how to use tests to assess if the results of your research are statistically significant. 

  You'll be able to determine the appropriate statistical test to use for a particular data set, and you'll know how to understand, calculate, and interpret effect sizes and confidence intervals. 

  You'll even know how to write the results of statistical analyses in APA format, one of the most popular and accepted formats for presenting the results of statistical analyses, which you can successfully adapt to other formats as needed. 

  Contents and Overview 

  This course begins with a brief introduction before diving right into the One Sample t Test, Independent Samples t Test, and Dependent Samples t Test. You'll use these tests to analyze differences and similarities between sample groups in a population. This will help you determine if you need to change your business plan for certain markets of consumers. 

  Next, you'll tackle how to use ANOVA (Analysis of Variance), including Post-hoc Tests and Levene's Equal Variance Test. These tests will also help you determine what drives consumer decisions and behaviors between different groups. 

  When ready, you'll master correlation and regression, as well as the chi-square. As with all previous sections, you'll see illustrations of how to analyze a statistical test, and you'll access additional examples for more practice. 

  Finally, you'll learn about data management in SPSS, including sorting and adding variables. 

  By the end of this course, you'll be substantially more confident in both IBM SPSS and statistics. You'll know how to use data to come to the right conclusions about your market. 

  By understanding how to use inferential statistics, you'll be able to identify consumer needs and come up with products and/or services that will address those needs effectively. 

Join the over 1,000 students who have taken this best-selling course - enroll today!

Statistics/Data Analysis with SPSS: Descriptive Statistics

Increase Your Descriptive Data Analytic Skills – Highly Valued And Sought After By Employers

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

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Students: 4967, Price: $74.99

Students: 4967, Price:  Paid

November, 2019.

Get marketable and highly sought after skills in this course that will increase your knowledge of data analytics, with a focus on descriptive statistics, an important tool for understanding trends in data and making important business decisions.  

Enroll now to join the more than 2000 students and get instant access to all course content!

Whether a student or professional in the field, learn the important basics of both descriptive statistics and IBM SPSS so that you can perform data analyses and start using descriptive statistics effectively. 

        By monitoring and analyzing data correctly, you can make the best decisions to excel in your work as well as increase profits and outperform your competition. 

        This beginner's course offers easy to understand step-by-step instructions on how to make the most of IBM SPSS for data analysis. 

  Make Better Business Decisions with SPSS Data Analysis 

  • Create, Copy, and Apply Value Labels

  • Insert, Move, Modify, Sort, and Delete Variables

  • Create Charts and Graphs

  • Measure Central Tendency, Variability, z-Scores, Normal Distribution, and Correlation

  Interpret and Use Data Easily and Effectively with IBM SPSS 

        IBM SPSS is a software program designed for analyzing data. You can use it to perform every aspect of the analytical process, including planning, data collection, analysis, reporting, and deployment. 

        This introductory course will show you how to use SPSS to run analyses, enter and code values, and interpret data correctly so you can make valid predictions about what strategies will make your organization successful. 

  Contents and Overview 

        This course begins with an introduction to IBM SPSS. It covers all of the basics so that even beginners will feel at ease and quickly progress. You'll tackle creating value labels, manipulating variables, modifying default options, and more. 

        Once ready, you'll move on to learn how to create charts and graphs, such as histograms, stem and leaf plots, and more. You'll be able to clearly organize and read data that you've collected. 

        Then you'll master central tendency, which includes finding the mean, median, and mode. You'll also learn how to measure the standard deviation and variance, as well as how to find the z-score. 

        The course ends with introductory statistics video lectures that dive deeper into graphs, central tendency, normal distribution, variability, and z-scores. 

        Upon completion of this course, you'll be ready to apply what you've learned to excel in your statistics classes and make smarter business decisions. You'll be able to use the many features in SPSS to gather and interpret data more effectively, as well as plan strategies that will yield the best results as well as the highest profit margins. 

Regression Analysis / Data Analytics in Regression

Gain Important and Highly Marketable Skills in Regression Analysis - Tame the Regression Beast Today!

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

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Students: 4231, Price: $89.99

Students: 4231, Price:  Paid

November, 2019.

Get marketable and highly sought after skills in this course while substantially increasing your knowledge of data analytics in regression. All course videos created and narrated by an award winning instructor and textbook author of quantitative methods.

This course covers running and evaluating linear regression models (simple regression, multiple regression, and hierarchical regression), including assessing the overall quality of models and interpreting individual predictors for significance. R-Square is explored in depth, including how to interpret R-Square for significance. Together with coverage of simple, multiple and hierarchical regression, we'll also explore correlation, an important statistical procedure that is closely related to regression. 

By the end of this course you will be skilled in running and interpreting your own linear regression analyses, as well as critically evaluating the work of others. Examples of running regression in both SPSS and Excel programs provided. Lectures provided in high quality, HD video with course quizzes available to help cement the concepts. Taught by a PhD award-winning university instructor with over 15 years of teaching experience. At Quantitative Specialists, our highest priority is in creating crystal-clear, accurate, easy-to-follow videos. 

Tame the regression beast once and for all – enroll today!

Dummy Variables in Regression Analysis

A Beginner's Guide

Created by LKB Training - Education, Training & Development

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Students: 3743, Price: $19.99

Students: 3743, Price:  Paid

Regression analysis is a flexible tool that can be adapted to suit different types of data. Using categorical variables as predictors increases the usefulness of regression models because we are often interested in addressing questions involving group differences. For instance, a marketing student may be interested in explaining how differences in race, gender, or region may affect customer attitude or behavior.

Unlike quantitative variables, the incorporation of qualitative explanatory variables in regression models requires a special type of variables known as dummy variables and a particular technique must be followed to quantitively represent the information appropriately.

In this course, you will learn how to use qualitative information in regression models through the application of dummy variables.

We will start by discussing the issues of using categorical variables in regression analysis. Then, definition and creation of dummy variables will be explained. Next, we will learn how to use dummy variables in regression models with real dataset. The final section of this course highlights some important considerations when using dummy variables such as dummy variables trap, interpreting logarithmic dependent variables, and the correct way to choose the reference group.

On completion of this course, you will be very confident in incorporating and interpreting dummy variables in multiple regression models.

SPSS Data Analysis for Beginning Researchers

Beginners/newbies: Working on your first data analysis but don't know where to start? This step-by-step guide can help.

Created by Dr. Haoran Zhang - Teacher, Researcher, and Data Analytics Expert

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Students: 3502, Price: $29.99

Students: 3502, Price:  Paid

Thank you for checking in SPSS Data Analysis for Beginning Researchers.

Who is this course for?

As the title implies, this course is for people working on their very first research projects (i.e. beginners / newbies), including but not limited to:

  • Students working on their research papers or dissertations

  • Beginning researchers with a non-technical background

  • Anyone curious about data analysis

What is so difficult about data analysis?

Many people find data analysis difficult, and with good reasons. Data analysis is difficult because it is not a single discipline. It is multi-disciplinary, which means that it requires integrated knowledge from different fields in order to do it right. Specifically, to conduct data analysis for your research you need:

  • Knowledge in the data analysis software (e.g. SPSS, Excel, R, etc.)

  • Knowledge in statistics concepts

  • Knowledge in research methods

  • Experience and skills working with data

What you need is not only knowledge in separate fields, but also experience and skills integrating these knowledge together to deal with real life data.

However, beginning researchers, by definition, have very little of these knowledge, experience, and skills. For example:

  • You may know how to use the data analysis software, but you don't know what method of analysis to use because you are not familiar with the statistics concepts.

  • You may know some statistics, but you may not know how to calculate the statistics on the computer.

  • You may have knowledge in both statistics and data analysis software, but you are not sure what analysis to conduct in order to fulfill the research needs.

  • You may have knowledge in statistics, software, and research, but you may not have the experience in actually handling data, and you are stuck dealing with practical issues here and there (such as missing and invalid data).

There are plenty of textbooks in these different disciplines, but few of them could teach you all these knowledge and skills. The problem is not lack of information. Quite the contrary, the problem is an overwhelmingly rich of information, so rich that you may not know where to start and how to select, so rich that you may not know how to put them into practice to fulfill your specific needs.

How may this course help?

This course is designed to be concise and practical. I am not attempting to tell you everything about statistics, SPSS, data analysis, and research - that would make your learning journey unnecessarily difficult. Instead, I am going to guide you, in an structured and practical way, through the minimal set of knowledge and skills you would need to analyze your own data. This course will not make you an expert in statistics, SPSS, data analysis, and research, but it will help you finish your own data analysis.

This is to be achieved by the following:

  1. Background knowledge. Each section of the course begins with a brief introduction to the minimal set of necessary statistics concepts you need.

  2. Practical demonstrations. All the videos are example-based. In each video, I show you how to conduct a practical data analysis task. These tasks are carefully selected from a list of most common analyses that you are likely to conduct.

  3. Experience sharing. In addition to statistics and SPSS, I also share a lot of my own experience doing research and data analysis, including how to deal with the most common issues while working with data, avoid the common mistakes and misunderstandings, and work around some annoying bugs in SPSS.

  4. Key points. Key points are highlighted throughout the video and also recapped at the end of the videos.

  5. Exercise. There is an exercise at the end of each section. This helps you apply what you have learned in the previous videos. There are also questions that prompt you to think deeper about what you are doing. The exercise problems have been used for a few years in my own offline classes so they are proven to be helpful to students. While appropriate, a separate video is dedicated to demonstrating the answers to these exercise problems.

  6. References. For those who would like to dig deeper into the statistics concepts, I have included links to useful references for your pursue.

So, how may I learn effectively in this course?

You may do the following for each section:

  1. Watch the videos. Take notes while necessary.

  2. Complete the exercise on your own. Knowing is not enough. We must apply!

  3. If you forget some of the details, refer back to the previous videos.

  4. After attempting the exercise, watch the next video for answers. Watch my steps carefully and compare with yours. In case of any difference, ask yourself which way is better, and why.

  5. Last but not least, apply the techniques to your own data.

Finally, if you have any questions about this course, or simply curious in what I do, you are welcome to follow me on Twitter: @phgod. I'll be happy to chat anything related to teaching, research, and data analysis.

That's all for the introduction. Happy learning!

Research Methods and Statistics: An Introduction

A Primer in Research Methodology and Statistics in the Social Sciences

Created by Monk Prayogshala - Not for Profit Academic Research Institution

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Students: 3407, Price: $89.99

Students: 3407, Price:  Paid

The Research Methodology and Statistical Reasoning Course includes topics ranging from what is a variable to, where can one use a two-way ANOVA. Statistics are widely used in social sciences, business, and daily life. Given the pervasive use of statistics, this course aims to train participants in the rationale underlying the use of statistics. This course aims to explain when to apply which statistical procedure, the concepts that govern these procedures, common errors when using statistics, and how to get the best analysis out of your data. Research methodology is used a base to explain statistical reasoning. The course also familiarises you with commonly used software for statistical analysis. The course will take 11 hours to complete, including one contact hour with the course instructor after completion of the workshop. The course is divided into 11 broad sections, which include 59 lectures and 21 quizzes. Participants would benefit from the course because understanding basic research methodology and statistics is essential prior to taking up any research-related endeavour. It is also an important part of the college curriculum from undergraduate to PhD levels. Designing research methods requires knowledge about various methods and understanding data. The comprehensive nature of the course ensures that students and professionals are not only able to understand, but also apply the course content. The course not only includes course content, but instructors that are approachable after completing it, who will provide feedback and address your specific needs.

IBM SPSS AMOS Foundation Course: SEM Scratch to Advanced

Learn Structural Equation Modelling, Path Analysis and Confirmatory Analysis using IBM SPSS AMOS from Scratch

Created by Scholarsight Learning - Courses in High Impact Research & Technology

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Students: 3194, Price: $99.99

Students: 3194, Price:  Paid

If you are looking to test a complex structural model then you already know the importance of AMOS. Its a powerful and one of the most popular tool for doing Structural Equation Modelling.

If you are a researcher then your knowledge of research will not be complete unless you mastered the SEM as vast majority of researches are increasingly using SEM. You can refer to my research papers that I have published using SEM:

  •  Sanjay Singh & Yogita Aggarwal (2017). Happiness at Work Scale: Construction and psychometric validation of a measure using mixed method approach. Journal of Happiness Studies. doi:10.1007/s10902-017-9882-x. Springer 
  •  Sanjay Singh & Yogita Aggarwal (2017). Antecedents and consequences of work significance in Indian organizations. Journal Management, Spirituality and Religion. doi: 10.1080/14766086.2017.1320580. Taylor & Francis 

In this course you will learn how to do SEM from scratch using AMOS. AMOS is a powerful tool for confirmatory validation and often used by researchers and psychometricians for research and high impact publishing. It enables you to specify, estimate, assess and present models to show hypothesized relationships among variables. The  AMOS software lets you build and test complex models more accurately and efficiently than standard multivariate statistics techniques. 

I am sure you will absolutely love this course. If not you can take your full refund within 30 days!! No questions asked!! 

I am very responsive to questions and in case you need any clarification I am just a message away. 

Some reviews from my SPSS Foundation course:

  • "Really Excellent in Explaining the topics each and every point step by step and I like his way of teaching approach.. I feel , it's very easy to understand the SPSS Tool in this way.. Thank You so much Dr. Sanjay Singh "
  • "Very well organized and easy to understand"
  • "its a must have course on SPSS. Excellent job by instructors! Trainer is very helpful n units are very well organized. Looking for more and more stuff from the trainer."

Sign up and Start learning AMOS the right way!! 

Statistics & Data Analysis: Linear Regression Models in SPSS

Beginner and Intermediate Data Analytic Methods for Testing Main Effects & Interactions with SPSS and the PROCESS Macro

Created by Andrew Luttrell, Ph.D. - Social Psychologist

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Students: 2732, Price: $24.99

Students: 2732, Price:  Paid

**Please note that this course was designed with the PROCESS macro version 2.13. Several aspects of the "interaction analysis" section of this course may currently be out of date with the most recent version of this add-on to SPSS.**

Linear regression is one of the essential tools in statistical analysis. In this course, we'll walk through step-by-step how to conduct many important analyses using SPSS.

Although you will learn the basics of what these statistics are, we'll avoid complicated mathematical discussions and go right to what you need to know to conduct these analyses.

Linear regression is basically a tool that allows you to test relationships between many variables at the same time, control for variables' effects, and create simple statistical models that allow you to make predictions.

In this course, we'll cover the following key topics:

  1. Correlations: You probably already know this, but understanding how to test the correlation between two variables gets us started in this course.

  2. Simple Linear Regression: Taking correlations one step further by creating a statistical model.

  3. Multiple Linear Regression: Being able to test multiple predictors at the same time and testing the unique effect of each.

  4. Hierarchical Linear Regression: How to test for the influence of different variables by adding them to the model one at a time.

  5. Interaction Analysis: How to test whether there's a two-way interaction between variables (also known as a "moderator" analysis)

You'll not only learn how to conduct these analyses, we'll also go over how to interpret the statistical results and how to graph the results using SPSS and a special Excel template I've created for you.

As a bonus, we also learn how to use a new free add-on to SPSS called "PROCESS," which simplifies a lot of the steps in doing interaction analysis in regression.

This course is meant to get you started in analyzing data using linear regression in SPSS. Whether you have data of your own that need to understand or you just want to know more about statistical data analysis, you'll get a running head start with this simple, easy-to-follow course.

I do linear regression analysis all the time in SPSS to conduct research in psychology, so I've become familiar with the steps it takes to pull off these analyses. I'm confident you will be able to, too!

The 16-hour SPSS Pro: Analysis, Interpretation, and Write-Up

16 Hours of Instruction From a 13 Year Researcher and College Instructor.

Created by Todd Bottom, Ph.D. - Founder Research Learning Center - Psychologist, Consultant, Educator

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Students: 1706, Price: $99.99

Students: 1706, Price:  Paid

Even after completing 8 years of college and taking 6-7 stats classes, conducting analyses and reporting results is without a doubt the most dreadful aspect of research for graduate students and many early career professionals. Are you wondering whether (or how) to check for normally distributed data? Can you use some help understanding how to interpret the amount of variance that is explained by your model and what to do with that information relative to your results? Are you wondering how to even set up your SPSS data file and checking for missing or outlying data before running your analyses?

Most of these skills (and many others that you will need for your graduate-level research) are not taught in classrooms, so it’s no wonder that so many graduate students struggle when it comes to the very important task of properly analyzing and reporting their research data. That’s why we designed this course….to fill those gaps that no one has showed you before.

Your instructor is Dr. Todd Bottom, a veteran researcher for 12 years who has worked in education, pharma research, consulting and dissertation coaching. Specific to this course, Todd also taught psychology classes at DePaul University in Chicago, including undergraduate statistics.

In this 16-hour extensive and comprehensive course on using SPSS, you will learn much more than simply what to click to run your analyses. Not only do we use a full data set with over 200 participants and 100 variables, the content runs from a basic understanding for newbies to understanding and reporting complex analyses such as cluster analysis and repeated measures ANOVA.

The course was designed to progress from a beginner level to gaining more advanced skills for those who are ready to conduct just about any analysis appropriate for doctoral-level work. For easy navigation in our systematic and comprehensive approach, the Modules and Lectures guide students through each of the program’s menu functions in the order that they are presented within the program’s platform.

The course was also designed to integrate a real classroom feel by offering lectures that are 30 minutes or longer.  So you don't have to scroll through dozens of 6-minute lessons to finally get to the information you need...simply start the lecture and get all of your information in one comprehensive lesson.  It is a great approach that lets students work through all aspects of an analysis from variable selection to interpreting and writing results.

We also include several quizzes after the modules to test your knowledge, and several homework assignments which allow students opportunities to use their newly gained skills in a practical manner. This course is the perfect solution to learning, conducting and reporting data analysis for nearly any student or researcher.  This includes....

  • If you are new to SPSS, the early modules will be a great learning resource as you learn the basics such as how to get a free trial of SPSS, how to properly import your data from an Excel file, how set up your complete variable information, and organizing a winning data file to eliminate a lot of wasted time later.

  • If you are somewhat familiar with SPSS but don’t have a lot of experience, this course will guide you through the most important aspects of completely and accurately running your analyses, whether you’re conducting t-tests, regressions, ANOVAs, or more sophisticated analyses such as cluster analysis or factor analysis. Along the way you will learn the differences between several types of (for example) regressions and t-tests, when to use a repeated measures analysis, and whether your data meet appropriate assumptions such as normal distribution of data.

  • If you have been familiar with SPSS for some time, the course will give you the benefit of having lifetime access that you can return to months or years later as a refresher. Have you ever learned information that you needed to know for just a short time and then forgotten much of it? When you purchase this course, you will never need to hunt down your old colleagues for help or to relearn everything needed to run statistical analyses because you will always have access to this library of step-by-step instructions and interpretations.

As for conducting statistical analyses, this course covers:

  • Running descriptive statistics and interpreting outputs for crosstabs, frequencies, means and standard deviations.

  • Conducting, interpreting and writing reliability analysis with Cronbach’s alpha

  • Two types of correlation analyses including bivariate and partial correlations.

  • Statistical tests to compare means with three different t-tests including one-samples, independent samples, and paired samples.

  • Conducting and interpreting outputs for three predictive (regression) analyses including linear regression, binary logistic regression, and multiple (stepwise) regression.

  • Four types of general linear modeling with ANOVA including one-way, univariate, multivariate, and repeated measures.

  • Conduct three types of classification analyses with K-means cluster analysis, hierarchical cluster analysis, and ROC curves.

  • Conducting, interpreting and reporting factor analysis with principal components analysis.

  • Analyzing and imputing missing data (and why this may not be a good idea for your study).

But this course is so much more than a step-by-step guide and simply clicking where needed to spit out results. You will also learn….

  • How and why to reverse score items as required.

  • The extreme importance of completely and properly setting up your variables before analysis.

  • Multiple ways to sum items for subscales and full measures, and the differences between the approaches.

  • How to check for outliers and extreme scores, and suggestions for handling them.

  • The differences between four types of missing data, and why they must be handled in different manners.

  • Recommendations for handling different types of missing data.

  • How to identify and report the amount of variance explained for several types of analyses.

For analyses that we run we discuss, the lectures also cover….

  • Multiple ways of checking normality of data.

  • Meeting assumptions such as multicollinearity and homogeneity of data.

  • Interpreting the outputs.

  • Writing results in APA format.

******************************************************

Praise for Todd's coaching and consulting...

Todd, you are amazing! I appreciate your editing services! The 1st line on my AQR review is “congrats for a strong 1st submission”. I actually had no dings on my grammar etc. (Doctoral Candidate, Arizona)

Todd surpasses all expectations! He has a wealth of knowledge and skill, provides high-quality professional products and is an absolute pleasure to work with. (Nonprofit Consultant, New York)

I highly recommend Dr. Bottom. He is innovative in his approach to solving problems, strategic, highly analytic and persistent.  Thanks Todd. (University Research Director, Atlanta)

Todd is a passionate and thorough consultant who came through for LCL when it counted most. He provided a comprehensive report that helped to strategically guide the organization through a critical transition period. (Nonprofit Owner, Chicago)

Statistics / Data Analysis: Survey Data and Likert Scales

How to Process Survey Data and Analyze Likert Scales In SPSS

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

"]

Students: 1589, Price: $89.99

Students: 1589, Price:  Paid

November, 2019.

This course takes the viewer through the key steps of entering and processing questionnaire/survey data and Likert scales in SPSS, including creating variables in SPSS, entering value labels, using statistical analyses to identify data entry errors, recoding Likert items, computing total (composite) scores, conducting reliability analyses of Likert scales, and computing other statistics, including frequencies, descriptive statistics (mean and standard deviation), and correlations. In addition to this, a number of additional database management skills in SPSS are also covered. Created by an award-winning university instructor with a focus on simple and accurate (step by step) explanations of the material.

                 Specifically, in this course you will learn the following: 

  • How to enter questionnaire data for qualitative and quantitative variables in SPSS

  • How to reverse code negatively-worded Likert scale items

  • How to create composite (total) scores in SPSS

  • How to conduct reliability analyses (coefficient alpha) in SPSS

  • How to use statistical analysis to detect data entry errors

  • How to use SPSS syntax to quickly and efficiently analyze data

  • How to score/recode true/false (dichotomous) data in SPSS

  • How to create professional looking Likert scales in Microsoft Word

  • Learn SPSS database management skills, including inserting variables and cases, recoding variables, applying value labels to several variables at once, handling missing values in SPSS, and more

  • Learn how to conduct statistical analyses in SPSS, including frequencies, descriptives, correlation, and more. (The primary focus of this course is on questionnaire/survey data and Likert scales; for a more detailed look at data analysis in SPSS, our courses descriptive and inferential statistics in SPSS courses are recommended)

                 This course is perfect for professionals looking to increase the data processing skills in SPSS, for those working on survey research, and for students working on theses or dissertations (or other research projects). 

Statistics / Data Analysis in SPSS: Factorial ANOVA

Applied data analysis in SPSS, covering the one-way ANOVA, two-way ANOVA (main effects and interaction), and more!

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

"]

Students: 1553, Price: $74.99

Students: 1553, Price:  Paid

November, 2019.

This course covers - step by step - a number of different ANOVAs and related statistical tests in SPSS. The following important statistical procedures are covered in the course:

1) One-way between ANOVA 

2) One-way within ANOVA

3) Post-hoc tests

4) Two-way between ANOVA (main effects, interaction effect, and simple effects)

5) Introduction to a three-way ANOVA

In completing this course, you will:

  • Learn how to write the results of statistical analyses in a professional "best practices" format.

  • Learn how to quickly recognize and interpret the most important information in statistical output.

  • Substantially increase your confidence in this highly respected subject matter. 

  • Increase your marketable quantitative job skills.

  • Learn how to use a common program for conducting statistical analyses: SPSS.

Designed by a award-winning (in teaching) statistics professor with a focus on both simple and accurate step-by-step explanations of the material. Substantially increase your knowledge of analysis of variance and inferential statistics -- enroll today!

Introduction to SPSS

An Introduction to the SPSS software program and basic descriptive and inferential statistics

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

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Students: 1339, Price: $49.99

Students: 1339, Price:  Paid

November, 2019

Course Description:

In this course, an introduction to the SPSS software program is provided. We'll take a look at how to get started in SPSS, including creating variables and entering data. After that, we'll cover creating value labels and entering some basic data. Modifying data files, including adding and sorting variables is then covered. After this, a number of descriptive statistics are covered, including bar graphs, stem and leaf plots, and measures of central tendency. Finally, the course concludes with hypothesis testing, with coverage of the Pearson r correlation coefficient.

IBM SPSS Modeler: Getting Started

Learn how to do Data Mining using IBM SPSS Modeler.

Created by Sandy Midili - Business Analytics Training Manager

"]

Students: 1131, Price: $49.99

Students: 1131, Price:  Paid

IBM SPSS Modeler is a data mining workbench that helps you build predictive models quickly and intuitively, without programming. Analysts typically use SPSS Modeler to analyze data by doing data mining and then deploying models.

Overview: This course introduces students to data mining and to the functionality available within IBM SPSS Modeler. The series of stand-alone videos, are designed to introduce students to specific nodes or data mining topics. Each video consists of detailed instructions explaining why we are using a technique, in what situations it is used, how to set it up, and how to interpret the results. This course is broken up into phases. The Introduction to Data Mining Phase is designed to get you up to speed on the idea of data mining. You will also learn about the CRISP-DM methodology which will serve as a guide throughout the course and you will also learn how to navigate within Modeler. The Data Understanding Phase addresses the need to understand what your data resources are and the characteristics of those resources. We will discuss how to read data into Modeler. We will also focus on describing, exploring, and assessing data quality. The Data Preparation Phase discusses how to integrate and construct data. While the Modeling Phase will focus on building a predictive model. The Evaluation Phase focuses how to take your data mining results so that you can achieve your business objectives. And finally the Deployment Phase allows you to do something with your findings.

SPSS Linear Regression Complete Tutorial with PhD Professor

Includes visusalizations, interactions, assumptions, data issues, power analysis, outliers, and detailed interpretations

Created by Stats Friend - Statistics and Research Consultant, I/O Psychologist

"]

Students: 1083, Price: $89.99

Students: 1083, Price:  Paid

In-depth modular class - learn only what you need! Includes optional modules for basics, advanced, & emergent problems.

Anyone can follow this step-by-step, end-to-end, in-depth tutorial for linear regression. The modular course covers all the possible pitfalls (well, pretty close), but in optional modules so you don't get bogged down with stuff you don't need.

I've poured all my consulting knowledge into this, even complex problems are covered in tremendous detail. However, you can skip the advanced information you don't need or want.

Topics Covered:

  • Data Prep

  • Missing Data

  • Descriptive Statistics

  • Checking Normality / Assumptions

  • Variable Transformation

  • Simple Linear Regression

  • Multiple Linear Regression

  • Univariate and Multivariate Outliers

  • Interactions / Moderation

  • Interpretation of Results

  • Scatter Plots

  • Line Graphs

  • Graphing Interactions

  • Multicollinearity

  • Variable Centering

  • Non-Linear Relationships

  • Pre- & Post-Hoc Power Analysis

  • Other Emergent Issues

Statistics / Data Analysis in SPSS: MANOVA

Applied Data Analysis Using Multivariate Analysis of Variance (MANOVA)

Created by Quantitative Specialists - Specializing in Statistics, Research Design, and Measurement

"]

Students: 979, Price: $74.99

Students: 979, Price:  Paid

November, 2019.

Multivariate Analysis of Variance, a popular but frequently perplexing procedure in statistics, is used to test two or more groups on two or more dependent variables. Mindful of the frustration and confusion that is often experienced with this procedure, this course was carefully designed by a specialist in quantitative methods (statistics) who has successfully taught MANOVA to graduate students from a variety of different backgrounds. Several students who thought they couldn’t understand this procedure were later explaining how they not only understood it, but actually found it to be fun!

Specifically, this course takes the viewer step-by-step through running and interpreting a number of different multivariate analyses of variance (MANOVA) in SPSS. Several different examples of MANOVA are covered, including:

 

  • MANOVA with 2 Groups (Also Known as Hotelling’s T-Squared)

     

  • MANOVA with 3 Groups

     

  • Post-Hoc Tests for Problems with 3 or More Groups

     

  • Two-way MANOVA

     

  • Equal Covariance Matrix Assumption of MANOVA Explained Step-by-Step

     

All tests include a detailed, step-by-step explanation of results, including how to assess the results for significance, with written results provided for each test covered.

 

Enroll today and be confused by MANOVA no longer!

SPSS Essentials: Statistics made easy

Master statistical tests without needing to learn complex equations. Learn how to analyse your research data with SPSS.

Created by Tendayi Viki - Academic, Author, Consultant and Entrepreneur

"]

Students: 935, Price: $24.99

Students: 935, Price:  Paid

Udemy is changing its pricing structure on April 4th when this course will increase to $20. Save money by buying it for $9 now.

How do you feel about statistics? Are you afraid you will pick the wrong test? Or make a mistake in your calculations and misinterpret your data? In short: are you afraid of stats?

If so, you've come to the right place! I'm here to demonstrate that your fear of statistics is unfounded.

Despite what many people think, you don't need to learn complex mathematical formulae to perform statistical analyses. You just need to learn two things.

  • First, you need to know how to choose the right statistical test.
  • Then, you need to know how to do the analysis in computer software like SPSS so you can draw conclusions from your data.

It's that easy!

This course will show you how to pick the right statistical test by answering four simple questions about your data and your research methodology. I call these the building blocks of statistical analysis, and it involves no maths at all.

Then you'll learn how to use SPSS to do the hard work for you. Even if you've never used SPSS, I'll help you get comfortable with the program. You'll learn how to open SPSS, enter data into the program and save it. Next you'll learn how to use SPSS to obtain descriptive statistics such as the mean, median, mode and frequencies. Then you'll discover how to use SPSS to calculate inferential statistics such as the t-test, correlation, Chi-square, ANOVA and regression.

The ability to perform quantitative data analysis is becoming an increasingly important skill for researchers to possess. Adding these skills to your CV will make you more employable and give you the confidence you need to start analysing your data today.

Psychometrics using SPSS and AMOS

Learn to develop a psychometric test from SCRATCH, Establish reliability and validity, do standardisation

Created by Scholarsight Learning - Courses in High Impact Research & Technology

"]

Students: 709, Price: $89.99

Students: 709, Price:  Paid

Psychological Testing is widely used in schools, colleges, companies, and institutions around the world. The entire discipline dealing with construction, validation and standardisation of psychological tests and such other assessment tools is known as psychometrics.

Psychometric testing is a big business and many big brands like Pearson, Thomas International, Prometric, Aon Hewitt, Ernst and Young, etc, are deeply involved into it. For Human Resource Managers psychometric skills are must but unfortunately MBA courses do not teach about psychometric testing as it's area of hard core quantitative psychologists. Sadly as per my experiences even many universities offering major in psychology do not train their students in psychometric assessment because quantitative psychology specialisations are not given in many universities.

Unfortunately, corporate world is flooded with poor tests without any rigour which reflects in poor hire or improper assessment of abilities. 

In this background, the course has been built to impart students with technical skills required to built a good psychometric test from scratch so that they can add real value to the intricate issue of assessing human abilities.

Its hands on course and my focus will be on skills part while discussing theory only as much as it is essential. 

Join the course now and start making yourself a skilled psychometrician today. 

SPSS for healthcare and life science statistics

Learn to conduct the most common statistical tests using SPSS

Created by Juan Klopper - Head of Postgraduate Research at the University of Cape Town

"]

Students: 438, Price: $24.99

Students: 438, Price:  Paid

If you want to analyze your own data or need to work in a research team that uses IBM's SPSS software, then this course is for you.

From the import of data, through descriptive statistics, data visualization, correlation, the comparison of means, and the analysis of categorical variables, this course will leave you familiar with the user interface and able to conduct all of the most common statistical tests.

IBM SPSS Statistics: Getting Started

Learn how to enter, manipulate, analyze, and report data using IBM SPSS Statistics.

Created by Sandy Midili - Business Analytics Training Manager

"]

Students: 216, Price: $49.99

Students: 216, Price:  Paid

Description: IBM SPSS Statistics addresses the entire analytical process, from planning to data collection to analysis, to reporting and deployment. Analysts typically use SPSS Statistics to analyze data by testing hypotheses and then reporting the results.

Overview: IBM SPSS Statistics: Getting Started is a series of self-paced videos (three hours of content). Students will learn the basics of using IBM SPSS Statistics for a typical data analysis session. Students will learn the fundamentals of reading data and assigning variable properties, data transformation, data analysis, and data presentation. Topics that you will learn will include:

  • Know the Basics steps of Analysis
  • Read Data and Assigning Variable Properties.
  • Use the Data Editor: Tools and Exporting Data
  • Summarize Individual Variables
  • Transform Data Values: Single Variables
  • Transform Data: Computing Variables
  • Describe Relationships Between Variables
  • Use Viewer Output Tools and Export Output

This is a first course in using IBM SPSS Statistics. You can begin with this course even if you have never used SPSS Statistics before. The course will not delve deeply into statistical theory, but it will provide a compelling, clear, head start into the fundamentals of using the software, taught by experts users who having been using SPSS Statistics everyday for many years.

IBM SPSS Modeler Essentials

Master various techniques in IBM SPSS Modeler to perform efficient analytics on your data

Created by Packt Publishing - Tech Knowledge in Motion

"]

Students: 151, Price: $89.99

Students: 151, Price:  Paid

IBM SPSS Modeler enables
you to explore data, identify important relationships that you can
leverage, and build predictive models quickly, allowing your
organization to base its decisions purely on the insights obtained from
your data.

With
the help of this course, you'll follow the industry-standard data mining
process, gaining new skills at each stage, from loading data to
integrating results into everyday business practices. Get a handle on
the most efficient ways of extracting data from your own sources,
preparing it for exploration and modeling. You will be acquainted with
the best methods for building models that will perform well in your
workplace.

Go beyond the basics and get the full power of your data mining workbench using IBM SPSS Modeler with this handy tutorial.

About the Author :

Jesus Salcedo has a Ph.D. in Psychometrics from Fordham University. He is an independent statistical consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.

KEITH MCCORMICK is a career-long practitioner of predictive analytics and data science. He has engaged in statistical modeling, data mining, and mentoring others in the area for more than 20 years. He has particular expertise in helping organizations perform their first predictive analytics project or build their first predictive analytics practice, and has done so in a variety of industries including healthcare, banking, telecommunications, non-profit, direct mail, pharmaceuticals, and retail. Keith is also an established author and speaker with four books in print or under contract. Although his consulting work is not restricted to any one tool, his writing and speaking have made him particularly well known in the IBM SPSS Statistics and IBM SPSS Modeler communities.

SPSS Amos – Test Models, Hypothesis, Validity (and More)

Learn Path Analysis, Mediation, Confirmatory Factor Analysis and More

Created by R Chandra, PhD - College Professor

"]

Students: 124, Price: $89.99

Students: 124, Price:  Paid

Do path analysis, test model fit, measure indirect effects, recognize and classify mediation types, recognize sources of bias in your estimates, perform confirmatory factor analysis, assess validity (construct, convergent and discriminant), combine path analysis with confirmatory factor analysis to build "full" structural equation models (that is path analysis with latent variables).

SPSS: Cleaning and Preparing Your Data For Accurate Analyses

Warning! Dirty data will invalidate your results and ruin your study!

Created by Todd Bottom, Ph.D. - Founder Research Learning Center - Psychologist, Consultant, Educator

"]

Students: 85, Price: $89.99

Students: 85, Price:  Paid

Praise for Todd's coaching and consulting...

Todd, you are amazing! I appreciate your editing services! The 1st line on my AQR review is “congrats for a strong 1st submission”. I actually had no dings on my grammar etc. (Doctoral Candidate, Arizona)

Todd surpasses all expectations! He has a wealth of knowledge and skill, provides high-quality professional products and is an absolute pleasure to work with. (Nonprofit Consultant, New York)

I highly recommend Dr. Bottom. He is innovative in his approach to solving problems, strategic, highly analytic and persistent.  Thanks Todd. (University Research Director, Atlanta)

Todd is a passionate and thorough consultant who came through for LCL when it counted most. He provided a comprehensive report that helped to strategically guide the organization through a critical transition period. (Nonprofit Owner, Chicago)

***********************************************************************************

About This Course

************************************************************************************

This course on data cleaning contains a great amount of detail and was designed to give you step-by-step examples for everything from anticipating data cleaning needs to determining what to do with missing data that will surely impress your colleagues and committee.  With our lectures we also provide the PowerPoint slides and other very helpful supporting materials that you can download to use for practice or for your own data project.

One of the most challenging yet rewarding academic experiences that one can accomplish is earning a doctoral degree.  However, many doctoral students - especially those in fully or partial online programs - struggle with the early stages of developing their dissertation.

It is extremely important to plan all aspects your dissertation study with an end goal in mind because decisions that you make during early stages can, and likely will, have an impact on later stages and the final production of your project.  This course is designed for students and professional researchers who are either about to begin analyzing their study data, or who are in the process of developing their data collection method.

However, the course is not limited to those who are in a doctoral program or who are conducting a dissertation project.  Others who will find the course to be helpful include undergraduate students, early career researchers, and those who wish to learn about the process of conducting rigorous research studies.

In addition to the technical skills, here is what you will get from the course:

  • Anticipate cleaning before or during collection

  • Why not all missing data are the same

  • Importance of recording the cleaning process and decisions

  • What part of cleaning to report in a manuscript

  • Understand reasons for deleting cases from your data

Learning IBM SPSS Statistics

Understand the basics of IBM SPSS Statistics to perform efficient data analysis with ease

Created by Packt Publishing - Tech Knowledge in Motion

"]

Students: 78, Price: $89.99

Students: 78, Price:  Paid

This video course consists
of step-by-step software demonstrations geared to familiarize new users
of IBM SPSS Statistics with this software. The first section focuses on
what IBM SPSS Statistics is, on what it does, who uses it, and how it
is used. The section then introduces new users to the IBM SPSS
Statistics user interface so they can become familiar with the windows,
menus, and dialog boxes that are part of the software. Finally, the
first section discusses the steps to analyzing data and some of the
typical analyses users might perform.

The
second section focuses on summarizing individual variables.
Specifically this section discuss some of the reasons users need to
summarize variables, and which summary statistics are relevant given the
type of data you are summarizing. This section also illustrates several
procedures, such as the Frequencies and Descriptives procedures, which
assist in providing summary statistics, and we will show how to obtain
confidence intervals. Finally, the Chart Builder is introduced so that
users can create pie charts, simple bar charts, and histograms.

The
third and final section of this video course shows users how to perform
and interpret the results of basic statistical analyses and graphical
displays. Users will learn when to use different statistical techniques,
how to set up different analyses, and how to interpret the results. The
third section begins by introducing the idea of inferential statistics
and hypothesis testing, and then moves on to discuss independent sample
t-tests, crosstabs and chi-square tests, as well as correlations. In
addition, visual displays are created so that users can better present
their findings by showing error bar charts, bar charts with a mean,
clustered bar charts, and scatterplots.

About the Author :

Jesus Salcedo has a Ph.D. in Psychometrics from Fordham University. He is an independent statistical consultant that has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.

Keith McCormick is a career long practitioner of predictive analytics and data science. He has engaged in statistical modeling, data mining, and mentoring others in the area for more than 20 years. He has a particular expertise in helping organizations perform their first predictive analytics project or build their first predictive analytics practice, and has done so in a variety of industries including
healthcare, banking, telecommunications, non-profit, direct mail, pharmaceuticals, and retail. Keith is also an established author and
speaker with four books in print, or under contract. Although his consulting work is not restricted to any one tool, his writing and
speaking has made him particularly well known in the IBM SPSS Statistics and IBM SPSS Modeler communities.

LEARNING PATH: Statistics and Data Mining for Data Science

Dive deep into the statistical and data mining techniques to get useful insights out of your data

Created by Packt Publishing - Tech Knowledge in Motion

"]

Students: 75, Price: $89.99

Students: 75, Price:  Paid

Data Science is an ever-evolving field. Data Science includes techniques and theories extracted from statistics, computer science, and machine learning. This video learning path will be your companion as you master the various data mining and statistical techniques in data science.

The first part of this course introduces you to the concept of data science, and explains the steps to analyse data and identify which summary statistics are relevant to the type of data you are summarizing. You will also be introduced to the idea of inferential statistics, probability, and hypothesis testing. You will then learn you will learn how to perform and interpret the results of basic statistical analyses such as chi-square, independent and paired sample t-tests, one-way ANOVA, etc. as well as using graphical displays such as bar charts and scatter plots.

The latter part of this course provides an overview of the various types of projects data scientists usually encounter. You will be introduced to the three methods (statistical, decision tree, and machine learning) with which you can perform predictive modelling. You will explore segmentation modelling to learn the art of cluster analysis, and will work with association modelling to perform market basket analysis using real-world examples.

By the end of this Learning Path, you will gain a firm knowledge on data analysis, data mining, and statistical analysis and be able to implement these powerful techniques on your data with ease.

Meet Your Expert(s):

We have the best works of the following esteemed author to ensure that your learning journey is smooth:

Jesus Salcedo has a PhD in Psychometrics from Fordham University. He is an independent statistical and data-mining consultant that has been analyzing data for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.

Statistics for healthcare professionals

A step by step course to understand the logic of medical statistics and master data analysis using SPSS and Jamovi softw

Created by Ahmed Mohamed Mukhtar Mukhtar - Professor at Faculty of Medicine Cairo University

"]

Students: 40, Price: $19.99

Students: 40, Price:  Paid

During my beginnings in medical school, I had to understand the concept of statistics in order to complete my Master and MD thesis but I had to work with many books and software in order to learn how to apply the appropriate statistical tests for my research. After finishing my MD, I decided to earn master’s degree in biomedical from the University of Newcastle. Although it is interesting, I have to understand a lot of formulas to get into the logic of statistical theory. After finishing my study, I dedicated my time to teach statistics to medical students in a way that they can understand the basics without getting in details of mathematical equations. If you are starting a research work related to health sciences and you find in statistics a difficult obstacle to jump, this is your course, which I have developed in a practical way with visual illustration.

Lessons outcome

By the end of this course, the students will be able to understand

  • How to describe the data

  • Relative risk and odds ratio

  • The difference between standard error and standard deviation

  • Why the confidence interval is really important

  • How to choose the statistical test

  • How to conduct common statistical tests such as  Paired and unpaired t test Mann Whitney U tets ANOVA Chi square

All examples mentioned in the course represent research questions and study designs that are frequently used in medical literature. Moreover, the course does not require any previous experience in statistical analysis, it will take the student step by step to understand basic terminologies that are frequently used in data analysis. Visual illustrations help the student to understand the output of statistical software without getting into the detail of statistical equation

Statistical software used in this course

The focus of current training program will be to help participants learn statistical skills through exploring SPSS and JAMOVI. The focus will be to develop practical skills of analyzing data, developing an independent capacity to accurately decide what statistical tests will be appropriate with a particular kind of research objective.

The learner will have the ability to choose to run all statistical analysis using either SPSS and/or Jamovi. All statistical analysis will be demonstrated via 13 exercises using two types of statistical software.

  • SPSS

  • Jamovi

Who this course is for:

  • Any healthcare professionals looking to understand basics of statistics

  • Faculty member looking to master SPSS and advance their data analysis required for conduction of medical research

  • Faculty member looking to master Jamovi and advance their data analysis required for conduction of medical research

Logistic Regression in SPSS for Social Science Research

Complete step by step guide on logistic regression in SPSS including interpretation and visualization

Created by Zvi Oduba - Local Government Analyst

"]

Students: 30, Price: $19.99

Students: 30, Price:  Paid

Social research with Logistic Regression in SPSS: A Complete Guide for the Social Sciences

The only course on Udemy that shows you how to perform, interpret and visualize logistic regression in SPSS, using a real world example, using the quantitative research process. Follow along with me as I talk you through everything you need to know to become confident in using regression analysis in your quantitative research report, dissertation or thesis. Perfect for those studying social science subjects or want to increase their statistical confidence and literacy.

What’s in the course?

  • Learn what logistic regression is, why it is so useful and why you should consider using it

  • Start to think critically about research questions, hypothesis, finding a dataset and thinking about variables. Follow along with an over-the-shoulder example

  • Learn how to perform a simple logistic regression in SPSS and how to interpret and visualize the findings

  • Learn how to perform multiple logistic regression in SPSS and make statistical conclusions

Don't fall for other courses that are over-technical, math's based and heavy on statistics! This course cuts all that out and explains in a way that is easy to understand!

Course outcomes

On completion of the course you will fully understand:

  • What logistic regression analysis is and what is used for

  • Learn how to formulate a research question and hypothesis

  • How to independently identify what data sources and variables are suitable for regression analysis

  • Learn how to import and clean your data in SPSS

  • Build your own logistic regression model in SPSS

  • How to interpret the results of a regression output

  • Interpret and visualize the findings from your model into your research report

  • increase your confidence in using quantitative data

    Learn this with a real world social science example, you can follow along with. This is the only course on Udemy that shows you from start to finish how regression analysis can be used in your research report from theory to practice.

Why take this course?

Logistics regression is a statistical model that is used to predict the probability of a certain outcome or event occurring, when that outcome or event is binary (such as pass/fail, true/false, healthy/sick). Logistic regression is used to describe the likelihood of something happening. Social researchers, social science students and academics are increasingly turning to quantitative methods such as logistic regression in their research because, given the right dataset, gives the opportunity to statistically quantify real world social issues.

Regression analysis is used to produce headlines like this:

  • Black people ‘40 times more likely’ to be stopped and searched in UK

  • Schools in poorer areas 4x more likely to have Higher grades downgraded

  • Teens who use e-cigarettes up to 5x time more likely to start smoking

Prospective employers are increasingly looking for students who are experienced in the social sciences but also are confident in data analysis techniques, like logistic regression. The Nuffield Foundation in the UK has highlighted the shortage of quantitatively-skilled social science students in the labour market and has since offered millions of pounds in funding to UK universities in a bid to increase knowledge in quantitative research methods.

Pre-requisites

This course is aimed at students, professionals and beginners in the field who want to begin using the power of logistics regression with SPSS into their study or work. Please don't be scared about statistics, there is NO math's involved in this course. Prior experience of some other quantitative methods and some use of SPSS would be useful, but it is definitely not essential. A passion for data analysis and research will make the process much more enjoyable! Good level of English and access to SPSS is required.