About this course: Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
Created by: Wesleyan University
Taught by: Lisa Dierker, Professor
Psychology
| Basic Info | Course 1 of 5 in the Data Analysis and Interpretation Specialization |
| Commitment | 4 weeks of study, 4-5 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Selecting a research question
We would like to welcome you to Wesleyan University's Data Analysis and Interpretation Specialization. In this session, we will discuss the basics of data analysis. Your task will be to select a data set that you would like to work with and to review available code books that help you develop your own research question. You will also set up a Tumblr blog that will allow you to reflect on these experiences, submit assignments and share your work with others throughout the course. First, you may want to check out the welcome video
5 videos, 6 readings
- Video: Welcome Video
- Lecture: A few quick questions to get started
- Video: Video Lesson - Steps in data analysis
- Video: Video Lesson - What do we mean by data?
- Video: Video Lesson - Datasets and codebooks
- Video: Video Lesson - Developing a research question
- Lecture: Course codebooks
- Lecture: Course Data Sets
- Lecture: Getting Set Up for the Assignments
- Lecture: Tumblr Instructions
- Lecture: Troubleshooting Your Tumblr Assignment Blog Link
Graded: Getting Your Research Project Started
WEEK 2
Writing your first program - SAS or Python
In this session, we will discuss how to write a basic program that allows you to load a data set and examine frequency distributions. Your task will be to write a program that helps you to explore the variables you have selected for your own research question. You may choose either Python or SAS. Both are made freely available, and we have created a helpful guide to support you in making the decision. Once you have selected your platform, just follow the instructions in the appropriate "GETTING STARTED...." file, and then check out this week's video lessons aimed at helping you write and run your first program. You need only view the lessons for one of the statistical platforms (SAS or Python).
8 videos, 7 readings
- Lecture: Choosing SAS or Python
- Lecture: Getting Started with SAS
- Lecture: Getting Started with Python
- Lecture: Codebook for Video Examples
- Lecture: Program for Video Examples
- Lecture: Uploading Your Own Data to SAS
- Video: SAS Lesson 1 - Defining exploratory data analysis
- Video: SAS Lesson 2 - SAS coding conventions
- Video: SAS Lesson 3 - Running your program and examining frequency distribution
- Video: SAS Lesson 4 - Refining your research question by selecting rows
- Video: Python Lesson 1 - Defining Exploratory Data Analysis
- Video: Python Lesson 2 - Python Coding Conventions
- Video: Python Lesson 3 - Running your program and examining frequency distributions
- Video: Python Lesson 4 - Refining your research question by selecting rows
- Lecture: Assignment Sample
Graded: Running Your First Program
WEEK 3
Managing Data
In this session, we will help you to make and implement even more decisions with data. Statisticians often call this task 'data management', while computer scientists like the term 'data munging'. Whatever you call it, it is a vital and ongoing process when working with data. Your task will be to write a program that manages the variables you have selected for your own research question.
8 videos, 3 readings
- Lecture: Program for Video Examples
- Lecture: Codebook for Video Examples
- Video: SAS Lesson 1 - Setting aside missing data
- Video: SAS Lesson 2 - Coding in valid data and recoding values
- Video: SAS Lesson 3 - Creating secondary variables
- Video: SAS Lesson 4 - Grouping variables within individual variables
- Video: Python Lesson 1 - Setting aside missing data
- Video: Python Lesson 2 - Coding valid data and recoding values
- Video: Python Lesson 3 - Creating secondary variables
- Video: Python Lesson 4 - Grouping values within individual variables
- Lecture: Assignment Sample
Graded: Making Data Management Decisions
WEEK 4
Visualizing Data
In this session we will discuss descriptive statistics and get you visualizing your newly data managed variables individually and as graphs showing the relationships between them.
12 videos, 4 readings
- Lecture: Graphing Decisions Flowchart
- Lecture: Programs for Video Examples
- Lecture: Codebooks for Video Examples
- Video: SAS Lesson 1 - Graphing individual variables
- Video: SAS Lesson 2 - Describing distributions visually
- Video: SAS Lesson 3 - Measures of center and spread
- Video: SAS Lesson 4 - Designing the role each of your variables will play
- Video: SAS Lesson 5 - Graphing decisions: categorical response variables
- Video: SAS Lesson 6 - Graphing decisions: quantitative response variable
- Video: Python Lesson 1 - Graphing individual variables
- Video: Python Lesson 2 - Describing distributions visually
- Video: Python Lesson 3 - Measures of Center and Spread
- Video: Python Lesson 4 - Designing the role each of your variables will play
- Video: Python Lesson 5 - Graphing Decisions: Categorical response variables
- Video: Python Lesson 6 - Graphing decisions: quantitative response variable
- Lecture: Assignment Sample
Graded: Creating graphs for your data
Supplemental Materials (All Weeks)
3 readings
- Lecture: How to Write a Literature Review
- Lecture: Translation Code
- Lecture: Acknowledgments
FAQs
How It Works
Travail en cours
Chaque cours fonctionne comme un manuel interactif en proposant des vidéos préenregistrées, des quiz et des projets.
Aide de la part de vos pairs
Connectez-vous à des milliers d'autres étudiants et débattez sur des idées, discutez le contenu du cours et obtenez de l'aide pour en maîtriser les concepts.
Certificats
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Creators
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.
Pricing
| Auditeur libre | Acheter le cours | |
|---|---|---|
| Accéder au contenu du cours | Available | Available |
| Accéder au contenu noté | Not available | Available |
| Recevoir une Note Finale | Not available | Available |
| Obtenir un Certificat de Cours partageable | Not available | Available |
Ratings and Reviews
The content is really well organized and very well presented.
I thought this course was great. It helped me get interested in python and think about data in a new way.
My name is Jose Antonio. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)
I did this course to get new knowledge about Big Data and Visualisation and better understand the technology and your practical applications.
The course was excellent and the classes well taught by teachers.
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AG
Es un curso interesante