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
Data Analysis Tools
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About this Course
4.5
332 ratings
Skills you will gain
Chi-Squared (Chi-2) DistributionData AnalysisStatistical Hypothesis TestingAnalysis Of Variance (ANOVA)
Syllabus - What you will learn from this course
Week
15 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.
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
Week
23 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.
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
Week
33 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.
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
Week
43 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.
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 ANOVA3m
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
4.5
76 Reviews33%
started a new career after completing these courses
38%
got a tangible career benefit from this course
20%
got a pay increase or promotion
Top Reviews
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.
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!
Instructors
Jen Rose
Research ProfessorPsychology
Lisa Dierker
ProfessorPsychology
About Wesleyan University
At Wesleyan, distinguished scholar-teachers work closely with students, taking advantage of fluidity among disciplines to explore the world with a variety of tools. The university seeks to build a diverse, energetic community of students, faculty, and staff who think critically and creatively and who value independence of mind and generosity of spirit.
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.
The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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