Think Stats

“Think Stats” is a comprehensive resource that delves into the realm of statistics through a practical and hands-on approach. The document explores fundamental statistical concepts and techniques, offering readers a clear understanding of statistical analysis. By utilizing real-world examples and exercises, “Think Stats” aims to demystify statistics and empower readers to apply statistical methods in various scenarios. With a focus on practicality and relevance, this source equips individuals with the knowledge and skills needed to interpret data, draw meaningful insights, and make informed decisions based on statistical analysis.

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Chapter 11 Regression

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The linear least squares fit in the previous chapter is an example of regression , which is the more general problem of fitting any kind of model to any kind of data. This use of the term “regression”...

Chapter 13 Survival analysis

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Survival analysis is a way to describe how long things last. It is often used to study human lifetimes, but it also applies to “survival” of mechanical and electronic components, or more generally to ...

Chapter 14 Analytic methods

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This book has focused on computational methods like simulation and resampling, but some of the problems we solved have analytic solutions that can be much faster. I present some of these methods in th...

Index

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Adams, Cecil, 2.11 Anaconda, 0.2 , 11.1 Australia, 5.1 abstraction, 5.7 accuracy, 11.9 acf, 12.7 addition, closed under, 14.1 adult height, 7 adult weight, 5.4 , 5.4 , 7 , 8.4 , 14.10 age, 10.2 , 11.1...

Chapter 10 Linear least squares

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The code for this chapter is in linear.py . For information about downloading and working with this code, see Section 0.2 . 10.1 Least squares fit Correlation coefficients measure the strength and sig...

Chapter 2 Distributions

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2.1 Histograms One of the best ways to describe a variable is to report the values that appear in the dataset and how many times each value appears. This description is called the distribution of the ...

Chapter 5 Modeling distributions

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The distributions we have used so far are called empirical distributions because they are based on empirical observations, which are necessarily finite samples. The alternative is an analytic distribu...

Chapter 9 Hypothesis testing

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The code for this chapter is in hypothesis.py . For information about downloading and working with this code, see Section 0.2 . 9.1 Classical hypothesis testing Exploring the data from the NSFG, we sa...

Chapter 0 Preface

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Think Stats is an introduction to the practical tools of exploratory data analysis. The organization of the book follows the process I use when I start working with a dataset: Importing and cleaning: ...

Chapter 12 Time series analysis

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A time series is a sequence of measurements from a system that varies in time. One famous example is the “hockey stick graph” that shows global average temperature over time (see https://en.wikipedia....

Chapter 6 Probability density functions

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The code for this chapter is in density.py . For information about downloading and working with this code, see Section 0.2 . 6.1 PDFs The derivative of a CDF is called a probability density function ,...

Chapter 7 Relationships between variables

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So far we have only looked at one variable at a time. In this chapter we look at relationships between variables. Two variables are related if knowing one gives you information about the other. For ex...