- Perhaps the most common and most…powerful statistical technique that we use is…Multiple Regression where several variables are used…collectively to predict scores on a single outcome variable,…a quantitative outcome usually.…In this example we're gonna be…using data about USJudgeRatings.…Let's take a quick look at that one…and this is where lawyers evaluated…forty three judges on twelve variables:…contact, integrity, demeanor, and so on,…finishing with worthy of retention,…which I'm going to be taking as the final outcome variable…that everything else seemed to fit into whether…they felt a judge was worthy of retention.…
Let's load the data here and take…a look at the first five cases.…All right, there we go...…The basic multiple regression's actually a…pretty simple process despite looking pretty long here.…What I'm doing is I'm going to be saving it as an object…because then you can get additional information about it.…I'm gonna be saving it as reg for reg1.…The basic function is lm for linear model…then what I'm going to do is I'm gonna just…
Author
Released
9/26/2013- Installing R on your computer
- Using the built-in datasets
- Importing data
- Creating bar and pie charts for categorical variables
- Creating histograms and box plots for quantitative variables
- Calculating frequencies and descriptives
- Transforming variables
- Coding missing data
- Analyzing by subgroups
- Creating charts for associations
- Calculating correlations
- Creating charts and statistics for three or more variables
- Creating crosstabs for categorical variables
Skill Level Intermediate
Duration
Views
Q: The R files within Chapters 01 to 10 don't appear to have any code in them. Where is the final code for each file?
A: Look in the "final" folder for each video. These folders contains the final R code written by the author.
Related Courses
-
Introduction
-
Welcome58s
-
-
1. Getting Started
-
Using RStudio4m 36s
-
Installing and managing packages11m 16s
-
Using built-in datasets in R5m 27s
-
Entering data manually4m 37s
-
Importing data8m 53s
-
Working with color in R10m 18s
-
2. Charts for One Variable
-
Overlaying plots7m 25s
-
Saving images5m 34s
-
Solution: Layering plots2m 22s
-
3. Statistics for One Variable
-
Calculating frequencies3m 33s
-
Calculating descriptives5m 43s
-
-
4. Modifying Data
-
Examining outliers6m 42s
-
Transforming variables9m 26s
-
Coding missing data6m 4s
-
-
5. Working with the Data File
-
Selecting cases5m 30s
-
Analyzing by subgroup3m 14s
-
Merging files5m 16s
-
-
6. Charts for Associations
-
Creating scatter plots5m 2s
-
7. Statistics for Associations
-
Calculating correlation3m 54s
-
Comparing proportions3m 34s
-
-
8. Charts for Three or More Variables
-
Creating 3D scatter plots5m 13s
-
9. Statistics for Three or More Variables
-
Conducting a cluster analysis14m 14s
-
Conclusion
-
Next steps3m 40s
-
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.
CancelTake notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.
Share this video
Embed this video
Video: Computing a multiple regression