From the course: Machine Learning & AI Foundations: Linear Regression
Unlock the full course today
Join today to access over 24,800 courses taught by industry experts.
Checking assumptions: Residuals plot - SPSS Tutorial
From the course: Machine Learning & AI Foundations: Linear Regression
Checking assumptions: Residuals plot
- [Instructor] Okay, we're gonna discuss a very important topic. A bit technical, a bit mysterious at first, but nonetheless terribly important, the notion of a residuals plot. So let's do an investigation of one using the MWBank dataset. So that's one of our case study datasets. Here's our data. A common trap that folks can fall into when they're new to multiple regression is that they hear about assumptions like, "Put all the relevant variables in," "leave the irrelevant variables out," "make sure that you have normality of errors," and it just sounds like this mysterious laundry list as if there's not much that we can do about it. There actually is, and the residuals plots are probably the key to understanding those assumptions. So let's take a closer look. We're gonna go into the regression menu. And because this set of menus can produce complex output, we're gonna start with just a simple regression example of this plot. We're gonna choose beginning salary as our dependent and…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
-
Challenges and assumptions of multiple regression8m 5s
-
(Locked)
Checking assumptions visually9m
-
(Locked)
Checking assumptions with Explore9m 55s
-
(Locked)
Checking assumptions: Durbin-Watson1m 55s
-
(Locked)
Checking assumptions: Levine's test4m 15s
-
(Locked)
Checking assumptions: Correlation matrix4m 31s
-
(Locked)
Checking assumptions: Residuals plot6m 23s
-
(Locked)
Checking assumptions: Summary3m 59s
-
-
-
-
-
-
-