Abstract
This chapter introduces data frames, random sampling, and correlation. Readers learn how to perform permutation tests to assess the significance of derived correlations.
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Your results will be different given the sampling.
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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 p-values and http://en.wikipedia.org/wiki/T-test on t-tests.
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© 2014 Springer International Publishing Switzerland
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Jockers, M.L. (2014). Correlation. In: Text Analysis with R for Students of Literature. Quantitative Methods in the Humanities and Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-03164-4_5
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DOI: https://doi.org/10.1007/978-3-319-03164-4_5
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03163-7
Online ISBN: 978-3-319-03164-4
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