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Inferential Statistics with R
- Welcome to Inferential Statistics with R
- Introduction to the Dataset
- Independent t-test
- Dependent t-test
- One-Way ANOVA
- Post Hoc Comparisons
- Other ANOVA Tests
- Dealing with Small Cells
- Linear Regression
- Multiple Regression
- Hierarchical Regression
- Extracting Output
- Reporting Results
- Testing Assumptions
- Testing for Normality
- Testing for Homogeneity of Variance
- Violated Assumptions
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This lesson is called Chi-Square, part of the Inferential Statistics with R course. This lesson is called Chi-Square, part of the Inferential Statistics with R course.
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## 1 ## tab2 <- college %>% tabyl(grade_class, live_on_campus) %>% janitor::chisq.test() tab2 ## 2 ## tab2$stdres tab2$observed tab2$expected
Perform a chi-square to examine how
live_on_campus. What is the p-value? Is there a relationship?
If there is a significant difference, examine standardized residuals and the observed/expected frequencies to determine what grade class is more or less likely to live on campus. Interpret the results.