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Comparing two means for paired samples (4)

Did you see how cumbersome this was? Calculating the 95% confidence interval, the t values and the p value can be done a lot easier using the built-in R function t.test(). This function outputs all these statistics in one go.

We have already used the function t.test() when working with independent group means. The function however works similar when working with paired samples. The main difference is that we need to set the argument pairs paired = TRUE because we are working with paired data. Also, as we are dealing with a dataframe that contains two vectors pre_weight and post_weight, you would need to specify the x and y arguments of the t.test() function, like so: t.test(x = pre_variable, y = post_variable)

This exercise is part of the course

Inferential Statistics

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Exercise instructions

  • Your console once again contains the weight dataframe which contains the variables pre_weight and post_weight. Use the function t.test() to perform a paired samples t.test. Don't forget to set the argument pairs paired = TRUE.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# perform a paired samples t test
Edit and Run Code