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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Simulating multiple tests


Each time the New Sample button is pressed, a pair of new samples from an exponential distribution with population means taken from the sliders are generated. The samples are plotted on a histogram and, underneath, a probability density function is drawn showing the standard error for the sample. As the confidence intervals are changed, observe how the acceptable deviation of the standard error changes as well.

Each time the button is pressed, we could think of it as a significance test with an alpha set to the complement of the confidence interval. In other words, if the probability distributions for the sample means overlap at the 95 percent confidence interval, we cannot reject the null hypothesis at the 5 percent significance level.

Observe how, even when the population means are identical, occasional large deviations in the means will occur. Where samples differ by more than our standard error, we can accept the alternate hypothesis. With a confidence level of...

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