Get access to all lessons in this course.
-
Welcome
- Welcome to Inferential Statistics with R
- Introduction to the Dataset
-
t-tests
- Independent t-test
- Dependent t-test
-
One-Way ANOVA
- One-Way ANOVA
- Post Hoc Comparisons
- Other ANOVA Tests
-
Chi-Square
- Chi-Square
- Dealing with Small Cells
-
Correlation
- Correlation
-
Regression
- Linear Regression
- Multiple Regression
- Hierarchical Regression
-
Reliability
- Reliability
-
Reporting Results
- Extracting Output
- Reporting Results
-
Testing Assumptions
- Testing Assumptions
- Testing for Normality
- Testing for Homogeneity of Variance
- Violated Assumptions
Inferential Statistics with R
Linear Regression
This lesson is locked
This lesson is called Linear Regression, part of the Inferential Statistics with R course. This lesson is called Linear Regression, part of the Inferential Statistics with R course.
Transcript
Click on the transcript to go to that point in the video. Please note that transcripts are auto generated and may contain minor inaccuracies.
Your Turn
Perform a linear regression examining how iq predicts act_reading. Ask for standardized coefficients before calling for the summary of results. Is IQ a significant predictor of ACT reading scores? If so, what is the standardized coefficient?
Learn More
Read more about the lm() function in the stats package. If you’d like to learn more, check out this tutorial in YaRrr! The Pirate’s Guide to R by Nathaniel D. Phillips.
Although not covered in these videos, it should be noted that all previously covered statistics up to this point are essentially linear models. This blog post by Dr. Athanasia Monika Mowinckel nicely illustrates how we could have done all the statistics using the lm() function instead.
You need to be signed-in to comment on this post. Login.