The Adventures of Stats Man and Model Hunter
1
Introduction
1.1
The power of repetition (and my…umm…
complicated
history with statistics)
1.2
But there’s a better way
2
Ethics
3
The Scientific Method
4
Univariate Distributions
4.1
Categorical Variables
4.1.1
Column Sorting
4.1.2
Visualizing
4.1.3
Pie Charts
4.1.4
Bar Charts
4.1.5
Interpreting Bar Charts
4.2
Example one
4.3
Example two
5
Univariate Estimates
6
Bivariate Visualizations
7
Bivariate Estimates
Diagnostics
7.1
Models are tools. And they don’t have feelings.
7.2
Residuals
7.3
Diagnostic tool # 1: Histogram of the residuals
7.3.1
Rant: Does Normality Really Matter?
7.3.2
Sensitivity Analyses
7.4
Diagnostic tool # 2: Residual Dependence (RD) Plot for Linearity
7.4.1
Statistical Models are Lazy
7.4.2
Residual Dependence Plots
7.4.3
How to Fix Nonlinearity
7.4.4
How to tell if nonlinearity is a problem?
7.4.5
How much nonlinearity is too much?
7.5
Diagnostic tool # 3: Scale-Location (SL) Plots for Homoscedasticity
7.5.1
Spread-Location (SL) Plots
7.6
Outliers
7.7
Independence
7.7.1
Why do models assume independence?
7.7.2
What happens if you violate the independence assumption?
7.7.3
How to detect and handle dependent data?
7.8
Summary
8
Probability
9
General Linear Models
Published with bookdown
The Adventures of Stats Man and Model Hunter
Chapter 9
General Linear Models