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Managing Data Analysis
  • Level Foundation
  • Duration 9 hours
  • Course by Johns Hopkins University
  • Offered by

About

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

Modules

Introduction

    • 1 Videos
    • 4 Readings
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1 Videos

  • What this Course is About

4 Readings

  • Pre-Course Survey
  • Course Textbook: The Art of Data Science
  • Conversations on Data Science
  • Data Science as Art

The Data Analysis Iteration

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Data Analysis Iteration

2 Videos

  • Data Analysis Iteration
  • Stages of Data Analysis

1 Readings

  • Epicycles of Analysis

Six Types of Questions

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Six Types of Questions

1 Readings

  • Six Types of Questions

Characteristics of a Good Question

    • 1 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Stating and Refining the Question

1 Videos

  • Characteristics of a Good Question

1 Readings

  • Characteristics of a Good Question

Exploratory Data Analysis

    • 1 Videos
    • 1 Readings
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1 Videos

  • Exploratory Data Analysis Goals & Expectations

1 Readings

  • EDA Check List

Using Models to Explore Your Data

    • 2 Videos
    • 2 Readings
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2 Videos

  • Using Statistical Models to Explore Your Data (Part 1)
  • Using Statistical Models to Explore Your Data (Part 2)

2 Readings

  • Assessing a Distribution
  • Assessing Linear Relationships

Exploratory Data Analysis: When to Stop

    • 1 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Exploratory Data Analysis

1 Videos

  • Exploratory Data Analysis: When to Stop

1 Readings

  • Exploratory Data Analysis: When Do We Stop?

Inference

    • 3 Videos
    • 2 Readings
Show info about module content

3 Videos

  • Making Inferences from Data: Introduction
  • Populations Come in Many Forms
  • Inference: What Can Go Wrong

2 Readings

  • Factors Affecting the Quality of Inference
  • A Note on Populations

Formal Modeling

    • 3 Videos
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3 Videos

  • General Framework
  • Associational Analyses
  • Prediction Analyses

Inference vs. Prediction: Implications for Modeling Strategy

    • 1 Videos
    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Inference
  • Formal Modeling, Inference vs. Prediction

1 Videos

  • Inference vs. Prediction

1 Readings

  • Inference vs. Prediction

Interpretation of Results

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Interpretation

1 Videos

  • Interpreting Your Results

1 Readings

  • Interpreting Your Results

Communication

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Communication

2 Videos

  • Routine Communication in Data Analysis
  • Making a Data Analysis Presentation

1 Readings

  • Routine Communication

Post-Course Survey

    • 1 Readings
Show info about module content

1 Readings

  • Post-Course Survey

Auto Summary

"Managing Data Analysis" is a focused one-week course designed to rapidly equip you with essential data analysis management skills. Led by experienced instructors, this course covers the iterative nature of data analysis, from formulating sharp questions to interpreting and presenting results. Ideal for business and management professionals, the course includes practical insights on directing analytic activities within a team. With a commitment of 4-6 hours, it's perfect for those seeking to enhance their data-driven decision-making abilities. Available on Coursera with a Starter subscription, this foundational course ensures you gain valuable knowledge without technical overload.

Jeff Leek, PhD
Instructors

Jeff Leek, PhD

Brian Caffo, PhD
Instructors

Brian Caffo, PhD

Roger D. Peng, PhD
Instructors

Roger D. Peng, PhD