EasyR: Using a General Linear Model (GLM) approach for simple regression and t-tests in R
Here we will introduce how we can use the General Linear Model (GLM) approach to create statistical models that allow us to examine bivariate relationships in numeric variables, as well as in categorical variables. Often these types of analysis are referred to as simple regression and t-tests, but we will see that a GLM approach accomplishes the same thing in an EasyR way.
Links to video sections and data files are in the description below.
Data files used in this video:
shoes_flipflops.csv: https://www.mediafire.com/file_premiu...
Sections:
00:00 Intro and loading prerequisites
02:20 Bivariate GLM for regression (numeric + numeric)
10:10 Interpreting the regression model coefficients
14:05 Obtaining a correlation coefficient
15:30 Regression model example 2
20:06 Bivariate GLM for t-test (numeric + categorical)
22:28 Interpreting the t-test model coefficients
25:10 Obtaining Cohen's d as a measure of effect size
29:13 t-test model example 2
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