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Welcome
- Welcome to Inferential Statistics with R
- Introduction to the Dataset
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t-tests
- Independent t-test
- Dependent t-test
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One-Way ANOVA
- One-Way ANOVA
- Post Hoc Comparisons
- Other ANOVA Tests
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Chi-Square
- Chi-Square
- Dealing with Small Cells
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Correlation
- Correlation
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Regression
- Linear Regression
- Multiple Regression
- Hierarchical Regression
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Reliability
- Reliability
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Reporting Results
- Extracting Output
- Reporting Results
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Testing Assumptions
- Testing Assumptions
- Testing for Normality
- Testing for Homogeneity of Variance
- Violated Assumptions
Inferential Statistics with R
Correlation
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This lesson is called Correlation, part of the Inferential Statistics with R course. This lesson is called Correlation, part of the Inferential Statistics with R course.
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Transcript
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Your Turn
Perform a correlation among the four ACT scores. Which two scales of the ACT have the highest correlation? Which two scales have the lowest correlation?
Learn More
Read more about the correlation functions in the rstatix package:
cor_mark_significant() to add significance levels
pull_triangle(), pull_upper_triangle(), and pull_lower_triangle()
cor_reorder() to reorder the matrix
cor_gather() and cor_spread() to reshape the correlation analysis results from matrix to list or vice versa
cor_as_symbols() to only show the symbols (e.g., ., +, *) in the matrix
cor_plot() to visualize the correlation matrix
For many other kinds of correlations (e.g., partial, Bayesian, multilevel, polychoric, biweight, percentage bend, Sheperd's Pi, distance), check out the correlation package.
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