Statistics: Foundations of Data Science, Part 6.

Course Description

Statistics is distinct from - but critical to - data science. In this non-technical, conceptual overview, you can learn how statistical practices such as data exploration, estimation, and feature selection give data science its power and insight. Statistics is the sixth of seven courses designed to outline the principles and practices of applied data science.

Course Information

  • Introductory level
  • 15 streaming video tutorials
  • 1 hour 18 minutes of instruction

Note. To navigate the videos, click on the menu icon (☰) in the top left of the video.

Table of Contents

1. INTRODUCTION

  1. Welcome (4:01)

2. EXPLORING DATA

  1. Exploration overview (2:23)
  2. Exploratory graphics (8:01)
  3. Exploratory statistics (5:05)
  4. Descriptive statistics (10:15)

3. INFERENCE

  1. Inferential statistics (4:28)
  2. Hypothesis testing (6:04)
  3. Estimation (8:04)

4. CHOICES

  1. Estimators (5:29)
  2. Measures of fit (3:30)
  3. Feature selection (6:15)
  4. Problems in modeling (5:58)
  5. Model validation (3:50)
  6. DIY (3:18)

5. CONCLUSION

  1. Next steps (1:43)