In this module, we are going to discuss and explore a statistical test used for “goodness of fit”. What does this mean? You know whether your shoes fit your feet based on whether they cause pain, right?
In sort of the same way, you can decide whether your data fits your expectations using a “goodness of fit” test. And believe me, if your data doesn’t fit, it can cause a lot of pain.
Note: for the chi-square section of the module, having a calculator on hand will make things go faster. You can also use a spreadsheet or calculator software on your computer.
1: Do those shoes fit?
2: Dilbert’s 3 day work week
3: The day is saved . or not
4: The Brute Force method
5: Computer = brute force
6: What's your threshold for pain?
7: Sick-day sistribution
8: A brief recap of the Brute Force Method
9: The Brute Force method again
10: Using arithmetic instead of Brute Force
11: One small correction
12: How big is big?
13: Degrees of Freedom
14: The magic lookup table
15: The answer, finally
16: Summary of chi-square
17: Another example for chi-square
18: So, which method do you like better?
20: Example 1: Testing for a dihybrid ratio
21: Example 2: Habitat selection (ecology)
22: Review and Words of Wisdom