Back to Managing Data Analysis
Johns Hopkins University

Managing Data Analysis

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

Status: Statistical Inference
Status: Workflow Management
Course9 hours

Featured reviews

ST

5.0Reviewed Nov 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

MB

5.0Reviewed Sep 3, 2017

One of the best courses I've taken. The instructor presented a clear approach and variety of suggestions for improving the consistency and quality of data science projects. Very useful!

MA

5.0Reviewed Jul 20, 2017

Excellent course! Highly recommend it.Dr. Peng covers the essentials of Managing Data Analysis in a balanced way, and empowers the data science manager/executive to be able to apply these right away.

JW

5.0Reviewed May 29, 2016

This is a challenging and excellent course ! This course really tunes you into the nuances of Data Analysis.I would recommend this course for anyone in Data Management.

GK

4.0Reviewed Sep 15, 2017

sometime it was not easy to understand the lecturer. also, it would be good to try some things out versus reading the expamples. other than that - a great course!

VW

5.0Reviewed Jan 31, 2017

Good review of the data analysis process, though it loses momentum when it gets into the communication & presentation areas. On to the next course in the specialization!

RD

4.0Reviewed Apr 6, 2019

This course is not for a person without any idea of Data analysis or Statistics. This course isn't for beginners. The content could have been presented even better with lucid examples.

SS

5.0Reviewed Sep 21, 2016

Great examples about difference between 'association' and 'predictive' understanding and pitfalls of decision making without knowing which one to be used where!

CT

5.0Reviewed Feb 7, 2020

Excellent course. Really enjoyed the instructor. Finally getting into some analysis. Made me want to refresh my stat skills and get working on a challenging project!

KL

5.0Reviewed Apr 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.

BC

4.0Reviewed Dec 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.

VG

4.0Reviewed Jul 25, 2017

Good overview of the process. Helped me in bridging data analysis processes with things that I already do as part of project management or business analytics/decision support projects.

All reviews

Showing: 20 of 476

Ying Chen
4.0
Reviewed Nov 28, 2015
Victor Ogeda
5.0
Reviewed May 5, 2020
Deleted Account
3.0
Reviewed Nov 2, 2016
Jordan Lee
2.0
Reviewed Nov 1, 2018
Sohail Butt
5.0
Reviewed Sep 7, 2017
Rebecca Taylor
5.0
Reviewed Sep 2, 2018
Kalindu Dissanayake
5.0
Reviewed Oct 23, 2022
JOMAR B. ABELLANA
5.0
Reviewed Apr 12, 2020
tommy cannady
5.0
Reviewed May 23, 2016
Arvind Kumar Srivastava
5.0
Reviewed Jun 4, 2020
Jason Campbell
5.0
Reviewed Nov 6, 2018
Omar Zaki
5.0
Reviewed Apr 12, 2019
Diego Serrano
5.0
Reviewed Oct 6, 2016
Daniel Setiawan
5.0
Reviewed Sep 15, 2020
Federico Javier Durán Franco
4.0
Reviewed Sep 14, 2020
Deleted Account
3.0
Reviewed Aug 8, 2016
Joe Bedale
5.0
Reviewed Apr 12, 2021
Tomas Kysela
5.0
Reviewed Jun 24, 2016
José Antonio Ribeiro Neto
5.0
Reviewed Jul 9, 2017
Jesus Pacheco
5.0
Reviewed Aug 1, 2017