À propos de ce cours : 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.
Créé par : Wesleyan University
Enseigné par : Jen Rose, Research Professor
Psychology
Enseigné par : Lisa Dierker, Professor
Psychology
| Informations de base | Cours 2 de 5 dans Data Analysis and Interpretation Specialization |
| Langue | English |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
| Notes des utilisateurs |
Programme de cours
SEMAINE 1
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 vidéos, 11 lectures
- Vidéo: Lesson 2 - From sample to population
- Vidéo: Lesson 3 - Steps in hypothesis testing
- Vidéo: Lesson 4 - What is a p value?
- Vidéo: Lesson 5 - How to choose a statistical test
- Vidéo: Lesson 6 - Ideas behind ANOVA
- Reading: Choosing SAS or Python
- Reading: Getting Started with SAS
- Reading: Getting Started with Python
- Reading: Course Codebooks
- Reading: Course Data Sets
- Reading: Uploading Your Own Data to SAS
- Reading: SAS Program Code for Video Examples
- Vidéo: SAS Lesson 7 - ANOVA: Explanatory variable with 2 levels
- Vidéo: SAS Lesson 8 - ANOVA: Explanatory variables with more than 2 levels
- Vidéo: SAS Lesson 9 - Post hoc tests for ANOVA
- Vidéo: SAS Lesson 10 - ANOVA summary
- Reading: Python Program Code for Video Examples
- Vidéo: Python Lesson 7 - ANOVA: Explanatory variables with two levels
- Vidéo: Python Lesson 8 - ANOVA: Explanatory variables with more than 2 levels
- Vidéo: Python Lesson 9 - Post hoc tests for ANOVA
- Vidéo: Python Lesson 10 - ANOVA Summary
- Reading: Getting set up for the assignments
- Reading: Tumblr Instructions
- Reading: Example: Running an analysis of variance
Noté: Running an analysis of variance
SEMAINE 2
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 vidéos, 3 lectures
- Reading: SAS Program Code for Video Examples
- Vidéo: SAS Lesson 2 - Chi Square Test of independence in practice
- Vidéo: SAS Lesson 3 - Post hoc tests for Chi Square tests of independence
- Vidéo: SAS Lesson 4 - Chi Square summary
- Reading: Python Program Code for Video Examples
- Vidéo: Python Lesson 2 - Chi Square test of independence in practice
- Vidéo: Python Lesson 3 - Post hoc tests for Chi Square tests of independence
- Vidéo: Python Lesson 4 - Chi Square summary
- Reading: Example: Running a Chi-Square Test of Independence
Noté: Running a Chi-Square Test of Independence
SEMAINE 3
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 vidéos, 2 lectures
- Vidéo: Lesson 2 - Correlation Example
- Reading: SAS Program Code for Video Examples
- Vidéo: SAS Lesson 3 - Calculating Correlation
- Reading: Python Program Code for Video Examples
- Vidéo: Python Lesson 3 - Calculating Correlation
Noté: Generating a Correlation Coefficient
SEMAINE 4
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 vidéos, 2 lectures
- Reading: SAS Program Code for Video Examples
- Vidéo: SAS Lesson 2 - Testing moderation in the context of ANOVA
- Vidéo: SAS Lesson 3 - Testing moderation in the context of chi square
- Vidéo: SAS Lesson 4 - Testing moderation in the context of correlation
- Vidéo: Python Lesson 1 - Defining moderation, a.k.a. statistical interaction
- Vidéo: Python Lesson 2 - Testing moderation in the context of ANOVA
- Vidéo: Python Lesson 3 - Testing moderation in the context of Chi-Square
- Vidéo: Python Lesson 4 - Testing moderation in the context of correlation
- Reading: Python Program Code for Video Examples
- Vidéo: A Question of Causation (Used with Permission from Annenberg Learner)
Noté: Testing a Potential Moderator
FAQ
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Créateurs
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.
Tarification
| Acheter le cours | |
|---|---|
| Accéder au contenu du cours | Disponible |
| Accéder au contenu noté | Disponible |
| Recevoir une Note Finale | Disponible |
| Obtenir un Certificat de Cours partageable | Disponible |
Notation et examens
Excellent course with clear explanation and practical work.
Good course, but need more direct feedback from professionals.
This is based on their previous course (Data Management and Visualization). This course is better in terms of explaining content clearly, and I enjoyed the real-life example used when explaining about the Chi Square test. However, the python coding could be more optimized; for example, it suggests doing the Chi Square post-hoc test for each variable one by one... which can be 15 batches of dictionary recodes! Thankfully someone in the forum provided a solution for doing an automated batch testing. Maybe the course lecturers felt that a batch recode would be too complicated, but it doesn't feel like you could use their method effectively for a work environment, either. In any case, it's still a good course to explain the various data tests for quantitative and categorical data if you're new to statistics.
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Good course