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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

The binomial distribution


The preceding histogram looks a great deal like a normal distribution, but in fact it is a binomial distribution. The two distributions are very similar, but the binomial distribution is used to model cases where we want to determine how many times a binary event is expected to occur.

Let's plot both the binomial and the normal distribution on a histogram to see how they compare:

(defn ex-4-9 []
  (let [passengers (concat (repeat 127 0)
                           (repeat 339 1))
        bootstrap (s/bootstrap passengers i/sum :size 10000)
        binomial (fn [x]
                   (s/pdf-binomial x :size 466 :prob (/ 339 466)))
        normal (fn [x]
                 (s/pdf-normal x :mean 339 :sd 9.57))]
    (-> (c/histogram bootstrap
                     :x-label "Female Survivors"
                     :series-label "Bootstrap"
                     :nbins 20
                     :density true
                     :legend true)
        (c/add-function binomial...
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