PURCHASE A DIGITAL COPY
PURCHASE A HARD COPY
|Lesson 1||Introduction to Statistical Research Methods|
|Lesson 2||Visualizing Data|
|Lesson 3||Central Tendency|
|Lesson 6||Normal Distribution|
|Lesson 7||Sampling Distributions|
|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 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