This course is part of the Executive Data Science Specialization

4.6
stars
3,185 ratings

Jeff Leek, PhD +2 more instructors

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Offered By

Executive Data Science SpecializationJohns Hopkins University

About this Course

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This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results. 
This is a focused course designed to rapidly get you up to speed on the process of data analysis and how it can be managed. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward.

After completing this course you will know how to….

1. Describe the basic data analysis iteration
2. Identify different types of questions and translate them to specific datasets
3. Describe different types of data pulls
4. Explore datasets to determine if data are appropriate for a given question
5. Direct model building efforts in common data analyses
6. Interpret the results from common data analyses
7. Integrate statistical findings to form coherent data analysis presentations

Commitment: 1 week of study, 4-6 hours

Course cover image by fdecomite. Creative Commons BY https://flic.kr/p/4HjmvD

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Course 3 of 5 in the

Executive Data Science Specialization

Approx. 9 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish, Japanese

What you will learn

Differentiate between various types of data pulls

Describe the basic data analysis iteration

Explore datasets to determine if data is appropriate for a project

Use statistical findings to create convincing data analysis presentations

Skills you will gain

Data Analysis
Communication
Interpretation
Exploratory Data Analysis

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 3 of 5 in the

Executive Data Science Specialization

Approx. 9 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish, Japanese

Instructors

Instructor rating

4.59/5 (239 Ratings)

Offered by

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Syllabus - What you will learn from this course

Content Rating95%(7,647 ratings)

Week

Week 1

9 hours to complete

Managing Data Analysis

Welcome to Managing Data Analysis! This course is one module, intended to be taken in one week. The course works best if you follow along with the material in the order it is presented. Each lecture consists of videos and reading materials that expand on the lecture. I'm excited to have you in the class and look forward to your contributions to the learning community. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!

9 hours to complete

19 videos (Total 144 min), 17 readings, 7 quizzes

19 videos

What this Course is About2m

Data Analysis Iteration8m

Stages of Data Analysis1m

Six Types of Questions6m

Characteristics of a Good Question6m

Exploratory Data Analysis Goals & Expectations11m

Using Statistical Models to Explore Your Data (Part 1)13m

Using Statistical Models to Explore Your Data (Part 2)5m

Exploratory Data Analysis: When to Stop6m

Making Inferences from Data: Introduction5m

Populations Come in Many Forms4m

Inference: What Can Go Wrong7m

General Framework8m

Associational Analyses10m

Prediction Analyses10m

Inference vs. Prediction12m

Interpreting Your Results10m

Routine Communication in Data Analysis6m

Making a Data Analysis Presentation5m

17 readings

Pre-Course Survey10m

Course Textbook: The Art of Data Science10m

Conversations on Data Science10m

Data Science as Art10m

Epicycles of Analysis10m

Six Types of Questions10m

Characteristics of a Good Question10m

EDA Check List10m

Assessing a Distribution10m

Assessing Linear Relationships10m

Exploratory Data Analysis: When Do We Stop?10m

Factors Affecting the Quality of Inference10m

A Note on Populations10m

Inference vs. Prediction10m

Interpreting Your Results10m

Routine Communication10m

Post-Course Survey10m

7 practice exercises

Data Analysis Iteration30m

Stating and Refining the Question30m

Exploratory Data Analysis30m

Inference30m

Formal Modeling, Inference vs. Prediction30m

Interpretation30m

Communication30m

Reviews

4.6

449 reviews

5 stars
67.43%
4 stars
24.95%
3 stars
5.69%
2 stars
1%
1 star
0.90%

HIGHLIGHTS

"Helpful quizzes" in 3 reviews

"Well-organized content" in 24 reviews

TOP REVIEWS FROM MANAGING DATA ANALYSIS

by BCDec 30, 2019

Like other reviewers said, this course is larger than the two previous courses. The content is excellent but I am giving 4/5 stars because I found many misspelled words throughout the course lectures.

by ELFeb 28, 2017

A long course compared to others in the specialization, but a lot of great material. Very well presented, the instructors know how to present this material and make it easy to grasp and understand.

by STNov 22, 2016

The course is full of the cases and the real life examples coupled with the theory background. Its very simple to understand and the course will definitely be of an value for people looking for

by KLApr 16, 2018

Great course for those who want a comprehensive overview of an analysis from A-Z. The professor explains each aspect in perfect detail, gives easy to understand examples, very comprehensive.

View all reviews

About the Executive Data Science Specialization

Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.

In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

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, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Managing Data Analysis