In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
This course is part of the Data Analysis and Interpretation Specialization
Offered By
Data Analysis and Interpretation SpecializationWesleyan UniversityAbout this Course
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Learner Career Outcomes
29%
started a new career after completing these courses
33%
got a tangible career benefit from this course
17%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
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Course 2 of 5 in the
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Approx. 10 hours to complete
English
Subtitles: English
Skills you will gain
Chi-Squared (Chi-2) DistributionData AnalysisStatistical Hypothesis TestingAnalysis Of Variance (ANOVA)
Learner Career Outcomes
29%
started a new career after completing these courses
33%
got a tangible career benefit from this course
17%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 5 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 10 hours to complete
English
Subtitles: English
Offered by
Wesleyan University
Wesleyan University, founded in 1831, is a diverse, energetic liberal arts community where critical thinking and practical idealism go hand in hand. With our distinctive scholar-teacher culture, creative programming, and commitment to interdisciplinary learning, Wesleyan challenges students to explore new ideas and change the world. Our graduates go on to lead and innovate in a wide variety of industries, including government, business, entertainment, and science.
Syllabus - What you will learn from this course
4 hours to complete
Hypothesis Testing and ANOVA
This session starts where the Data Management and Visualization course left off. Now that you have selected a data set and research question, managed your variables of interest and visualized their relationship graphically, we are ready to test those relationships statistically. The first group of videos describe the process of hypothesis testing which you will use throughout this course to test relationships between different kinds of variables (quantitative and categorical). Next, we show you how to test hypotheses in the context of Analysis of Variance (when you have one quantitative variable and one categorical variable). Your task will be to write a program that manages any additional variables you may need and runs and interprets an Analysis of Variance test. Note that if your research question does not include one quantitative variable, you can use one from your data set just to get some practice with the tool. If your research question does not include a categorical variable, you can categorize one that is quantitative.
4 hours to complete
14 videos (Total 79 min), 11 readings, 1 quiz
14 videos
Lesson 2 - From sample to population5m
Lesson 3 - Steps in hypothesis testing7m
Lesson 4 - What is a p value?5m
Lesson 5 - How to choose a statistical test1m
Lesson 6 - Ideas behind ANOVA9m
SAS Lesson 7 - ANOVA: Explanatory variable with 2 levels6m
SAS Lesson 8 - ANOVA: Explanatory variables with more than 2 levels2m
SAS Lesson 9 - Post hoc tests for ANOVA5m
SAS Lesson 10 - ANOVA summary2m
Python Lesson 7 - ANOVA: Explanatory variables with two levels8m
Python Lesson 8 - ANOVA: Explanatory variables with more than 2 levels3m
Python Lesson 9 - Post hoc tests for ANOVA5m
Python Lesson 10 - ANOVA Summary3m
11 readings
Choosing SAS or Python10m
Getting Started with SAS10m
Getting Started with Python10m
Course Codebooks10m
Course Data Sets10m
Uploading Your Own Data to SAS10m
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Getting set up for the assignments10m
Tumblr Instructions10m
Example: Running an analysis of variance10m
2 hours to complete
Chi Square Test of Independence
This session shows you how to test hypotheses in the context of a Chi-Square Test of Independence (when you have two categorical variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a Chi-Square Test of Independence. Note that if your research question only includes quantitative variables, you can categorize those just to get some practice with the tool.
2 hours to complete
7 videos (Total 48 min), 3 readings, 1 quiz
7 videos
SAS Lesson 2 - Chi Square Test of independence in practice5m
SAS Lesson 3 - Post hoc tests for Chi Square tests of independence10m
SAS Lesson 4 - Chi Square summary1m
Python Lesson 2 - Chi Square test of independence in practice8m
Python Lesson 3 - Post hoc tests for Chi Square tests of independence8m
Python Lesson 4 - Chi Square summary1m
3 readings
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Example: Running a Chi-Square Test of Independence10m
2 hours to complete
Pearson Correlation
This session shows you how to test hypotheses in the context of a Pearson Correlation (when you have two quantitative variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a correlation coefficient. Note that if your research question only includes categorical variables, you can choose other variables from your data set just to get some practice with the tool.
2 hours to complete
4 videos (Total 18 min), 2 readings, 1 quiz
4 videos
Lesson 2 - Correlation Example3m
SAS Lesson 3 - Calculating Correlation4m
Python Lesson 3 - Calculating Correlation4m
2 readings
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
2 hours to complete
Exploring Statistical Interactions
In this session, we will discuss the basic concept of statistical interaction (also known as moderation). In statistics, moderation occurs when the relationship between two variables depends on a third variable. The effect of a moderating variable is often characterized statistically as an interaction; that is, a third variable that affects the direction and/or strength of the relation between your explanatory (X) and response (Y) variable. Your task will be to test your own research question in the context of one or more potential moderating variables.
2 hours to complete
9 videos (Total 51 min), 2 readings, 1 quiz
9 videos
SAS Lesson 2 - Testing moderation in the context of ANOVA4m
SAS Lesson 3 - Testing moderation in the context of chi square6m
SAS Lesson 4 - Testing moderation in the context of correlation4m
Python Lesson 1 - Defining moderation, a.k.a. statistical interaction4m
Python Lesson 2 - Testing moderation in the context of ANOVA4m
Python Lesson 3 - Testing moderation in the context of Chi-Square4m
Python Lesson 4 - Testing moderation in the context of correlation4m
A Question of Causation (Used with Permission from Annenberg Learner)14m
2 readings
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Reviews
TOP REVIEWS FROM DATA ANALYSIS TOOLS
by DLDec 19, 2015
Again, with no formal SAS training and minimal statistics background. I found taking the first course and then this course - week after week my knowledge grew in a consistent and organized fashion.
by ASFeb 9, 2017
This was good module. It covers the basics of inferential statistical techniques along with its application using SAS/Python. I would definitely recommend to take up if you are a beginner.
by AMDec 2, 2015
Very good for beginners. concept explanation as well as coding were great. doesn't take too long to finish. I enrolled regression modeling course by Wesleyan and waiting to start.
by GROct 4, 2017
Just love this whole specialisation! videos are great, lessons are great... it's just a great course! highly recommended to anyone looking to dive into the field of data analysis!
About the Data Analysis and Interpretation Specialization
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
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