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-
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
Independent t-test
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This lesson is called Independent t-test, part of the Inferential Statistics with R course. This lesson is called Independent t-test, part of the Inferential Statistics with R course.
Transcript
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Your Turn
Perform an independent samples t-test to test whether there is a difference in
exam_1
byathlete
. Usevar.equal = TRUE
. Is there a difference? What is the p-value?Perform an independent samples t-test to test whether there is a difference in
act_english
bygender
. Usevar.equal = TRUE
. Is there a difference? What is the p-value?
Notice what happens since gender has 3 levels. Try out using the filter()
function from dplyr
to only check the difference between Female and Male students. Alternatively, check out the page on t_test()
to see how to use the comparisons
argument to specify the groups to compare.
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