Street-Smart Stats cover
Lesson 1 Introduction to Statistical Research Methods
Lesson 2 Visualizing Data
Lesson 3 Central Tendency
Lesson 4 Variability
Lesson 5 Standardizing
Lesson 6 Normal Distribution
Lesson 7 Sampling Distributions
Lesson 8 Estimation
Lesson 9 Hypothesis Testing
Lesson 10 t-Tests for Dependent Samples
Lesson 11 t-Tests for Independent Samples
Lesson 12 Intro to One-Way ANOVA
Lesson 13 One-Way ANOVA: Test significance of differences
Lesson 14 Correlation
Lesson 15 Linear Regression
Lesson 16 Chi-Squared Tests

You’ve now learned many methods of using statistics to analyze data and draw conclusions. However, that’s the easy part. The hard part is determining which test to use and for what purposes. For example:

  • At-risk youth go through summer chess programs with mentors. How would you test whether or not the summer chess program helped at-risk youth perform better in school?
  • You’re curious to know how chivalry towards women is changing as more women reach leadership positions in the corporate world. How would you measure “chivalry”? What data would you collect and where would you obtain your sample?
  • You want to know how educational attainment differs by the predominant sector (agriculture, services, or industry) of the area in which subjects live. What test(s) would you use?

Hopefully, whenever you read any conclusions based on statistics tests you’ll be able to critique the methodologies used. In turn, you’ll get better and better at determining robust statistical research methods.

The journey doesn’t end here. Feel free to post any questions about statistics below.


Data sets used throughout the course
Fortune 500
State data

Additional resources:

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