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Data Analysis with R, Second Edition

You're reading from   Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Length 570 pages
Edition 2nd Edition
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Author (1):
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Tony Fischetti Tony Fischetti
Author Profile Icon Tony Fischetti
Tony Fischetti
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Table of Contents (19) Chapters Close

Preface 1. RefresheR FREE CHAPTER 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 18. Other Books You May Enjoy

Testing two means


An even more common hypothesis test is the independent samples t-test. You would use this to check the equality of two samples' means. Concretely, an example of using this test would be if you have an experiment where you are testing to see if a new drug lowers blood pressure. You would give one group a placebo and the other group the real medication. If the mean improvement in blood pressure was significantly greater than the improvement with the placebo, you might infer that the blood pressure medication works. Outside of more academic uses, web companies use this test all the time to test the effectiveness of, for example, different internet ad campaigns; they expose random users to either one of two types of ads and test if one is more effective than the other. In web-business parlance, this is called an A-B test, but that's just business-ese for controlled experiment.

The term independent means that the two samples are separate, and that data from one sample doesn't...

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