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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Measuring t-statistics and p-values using Python

Let's fabricate some experimental data and use the t-statistic and p-value to determine whether a given experimental result is a real effect or not. We're going to actually fabricate some fake experimental data and run t-statistics and p-values on them, and see how it works and how to compute it in Python.

Running A/B test on some experimental data

Let's imagine that we're running an A/B test on a website and we have randomly assigned our users into two groups, group A and group B. The A group is going to be our test subjects, our treatment group, and group B will be our control, basically the way the website used to be. We'll set this up with the following...

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