Continuing the playlist on Regression, I have uploaded a new video to YouTube:
Regression -- Part 4: Multiple Linear. There are 5 Keys to Understanding, here is the 3rd. See the Videos pages of this website for more info on available and planned videos.
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Categorical Variables are used in ANOMA, ANOVA, with Proportions, and in the Chi-Square Tests for Independence and Goodness of Fit. Categorical Variables are also known as "Nominal" (named) Variables and "Attributes" Variables. The concept can be confusing, because the values of a Categorical Variable are not numbers, but names of categories. The numbers associated with Categorical Variables come from counts of the data values within a named category. Here's how it works:- In this example there are two
__Categorical Variables__, "Gender" and "Ice Cream (flavor)". - The
__values__of the two Categorical Variables are the__names of the categories__for the Variable. For example, the Categorical Variable "Gender" has 2 possible values: "female" and "male". - If we're going to use these Variables in a Chi-Square Test for Independence, for example, we need to have some numbers. The
__numbers are the counts__of the data values in each category. For example, the count of persons whose gender is "female" and whose favorite ice cream flavor is "vanilla" is 25.
Continuing the playlist on Regression, I have uploaded a new video to YouTube:
. It talks about things that are required for all 3 types of Regression covered in the book -- Simple Linear, Multiple Linear, and Simple Nonlinear Regression. Topics include clip levels for R squared, Residuals, establishing Cause and Effect, and the dangers of Extrapolation.Regression Part 3: Analysis Basics See the page of this website for the status of completed and planned videos.videos |
## AuthorAndrew A. (Andy) Jawlik is the author of the book, Statistics from A to Z -- Confusing Concepts Clarified, published by Wiley. ## Archives
July 2019
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