This course is part of the Data Analysis and Interpretation Specialization

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916 ratings

Lisa Dierker

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Data Analysis and Interpretation SpecializationWesleyan University

About this Course

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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.

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Shareable Certificate

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Course 1 of 5 in the

Data Analysis and Interpretation Specialization

Approx. 12 hours to complete

English

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Skills you will gain

SAS Language
Data Analysis
Python Programming
Data Management

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Data Analysis and Interpretation Specialization

Approx. 12 hours to complete

English

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Try Coursera for Business

Instructor

Instructor rating

4.51/5 (67 Ratings)

Lisa Dierker

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.

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Syllabus - What you will learn from this course

Content Rating94%(5,379 ratings)

Week

Week 1

2 hours to complete

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

2 hours to complete

5 videos (Total 31 min), 5 readings, 1 quiz

Week

Week 2

3 hours to complete

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).

3 hours to complete

8 videos (Total 58 min), 8 readings, 1 quiz

8 videos

SAS Lesson 1 - Defining exploratory data analysis3m

SAS Lesson 2 - SAS coding conventions8m

SAS Lesson 3 - Running your program and examining frequency distribution9m

SAS Lesson 4 - Refining your research question by selecting rows5m

Python Lesson 1 - Defining Exploratory Data Analysis3m

Python Lesson 2 - Python Coding Conventions9m

Python Lesson 3 - Running your program and examining frequency distributions10m

Python Lesson 4 - Refining your research question by selecting rows7m

8 readings

Choosing SAS or Python10m

Getting Started with SAS10m

Getting Started with Python10m

Codebook for Video Examples10m

SAS Program for Video Examples10m

Python Program for Video Examples10m

Uploading Your Own Data to SAS10m

Assignment Sample10m

Week

Week 3

2 hours to complete

Managing Data

2 hours to complete

8 videos (Total 45 min), 4 readings, 1 quiz

8 videos

SAS Lesson 1 - Setting aside missing data6m

SAS Lesson 2 - Coding in valid data and recoding values2m

SAS Lesson 3 - Creating secondary variables7m

SAS Lesson 4 - Grouping variables within individual variables2m

Python Lesson 1 - Setting aside missing data7m

Python Lesson 2 - Coding valid data and recoding values6m

Python Lesson 3 - Creating secondary variables8m

Python Lesson 4 - Grouping values within individual variables3m

4 readings

SAS Program for Video Examples10m

Python Program for Video Examples10m

Codebook for Video Examples10m

Assignment Sample10m

Week

Week 4

4 hours to complete

Visualizing Data

4 hours to complete

12 videos (Total 108 min), 5 readings, 1 quiz

12 videos

SAS Lesson 1 - Graphing individual variables6m

SAS Lesson 2 - Describing distributions visually7m

SAS Lesson 3 - Measures of center and spread11m

SAS Lesson 4 - Designing the role each of your variables will play5m

SAS Lesson 5 - Graphing decisions: categorical response variables13m

SAS Lesson 6 - Graphing decisions: quantitative response variable9m

Python Lesson 1 - Graphing individual variables6m

Python Lesson 2 - Describing distributions visually7m

Python Lesson 3 - Measures of Center and Spread11m

Python Lesson 4 - Designing the role each of your variables will play5m

Python Lesson 5 - Graphing Decisions: Categorical response variables14m

Python Lesson 6 - Graphing decisions: quantitative response variable10m

5 readings

Graphing Decisions Flowchart10m

SAS Programs for Video Examples10m

Python Programs for Video Examples10m

Codebooks for Video Examples10m

Assignment Sample10m

1 hour to complete

Supplemental Materials (All Weeks)

1 hour to complete

3 readings

Reviews

4.4

265 reviews

5 stars
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4 stars
24.48%
3 stars
6.12%
2 stars
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1 star
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TOP REVIEWS FROM DATA MANAGEMENT AND VISUALIZATION

by NZAug 24, 2020

Overall the course was great because it taught me a lot about the "analysis logic". From this course I know how analysis a data visually using python language.

by ARJun 1, 2020

I learnt a lot from this course in data management and visualization and enjoyed the assignment parts of the course. I also gained insights in making data management decisions!

by SPJun 25, 2018

This is a great course for beginners. The course instructors have arranged the course at a very comfortable pace and this is a great beginning point for anyone who wants to learn SAS or Python.

by RSJun 13, 2016

It was a great course for me! It gives a very important basic of statistic & visualization.

I really appreciated the way it was presented.

View all reviews

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?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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