Abstract
This chapter introduces data frames, random sampling, and correlation. Readers learn how to perform permutation tests to assess the significance of derived correlations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Another way to test the significance of a correlation coefficient is to use the cor.test function. Use ?cor.test to learn about this function and then run it using the method = "pearson" argument. To make more sense out of the results, consider consulting http://en.wikipedia.org/wiki/P-value on t-tests.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
L. Jockers, M., Thalken, R. (2020). Correlation. In: Text Analysis with R. Quantitative Methods in the Humanities and Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-39643-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-39643-5_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-39642-8
Online ISBN: 978-3-030-39643-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)