Statistical analysis allows you both to simplify your data through descriptive procedure and to amplify your data through inference. Learn how statistics allows you go go from the data in hand to make valid inferences about broader groups. In this course you'll learn about exploratory data analysis, estimation, and critical procedures like cluster analysis and principal component analysis, all of which combine to give you critical insight into your data.

COURSE INFORMATION
  • Introductory level
  • 15 streaming video tutorials
  • 1 hour 18 minutes of instruction
  • Downloadable keypoints PDFs (available soon)
  • Downloadable workbook PDFs (available soon)
  • Created by Barton Poulson, PhD

COURSE BUNDLES

This course is available for purchase as an individual course or as part of the discounted course bundle Foundations of Data Science.

Course Curriculum

  • 1

    Introduction

    • Welcome
  • 2

    Exploring Data

    • Exploration overview

    • Exploratory graphics

    • Exploratory statistics

    • Descriptive statistics
  • 3

    Inference

    • Inferential statistics

    • Hypothesis testing

    • Estimation
  • 4

    Choices

    • Estimators

    • Measures of fit

    • Feature selection

    • Problems in modeling

    • Model validation

    • DIY
  • 5

    Conclusion

    • Next steps

About the instructor

Founder

Barton Poulson

Bart is the founder of datalab.cc and an advocate for data science and data literacy. He has taught people to work with data for over twenty years as a university professor, online instructor, consultant, collaborator, and author. Bart lives with his family in Salt Lake City.

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