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15 Math Concepts Every Data Scientist Should Know

You're reading from   15 Math Concepts Every Data Scientist Should Know Understand and learn how to apply the math behind data science algorithms

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781837634187
Length 510 pages
Edition 1st Edition
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Author (1):
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David Hoyle David Hoyle
Author Profile Icon David Hoyle
David Hoyle
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Essential Concepts
2. Chapter 1: Recap of Mathematical Notation and Terminology FREE CHAPTER 3. Chapter 2: Random Variables and Probability Distributions 4. Chapter 3: Matrices and Linear Algebra 5. Chapter 4: Loss Functions and Optimization 6. Chapter 5: Probabilistic Modeling 7. Part 2: Intermediate Concepts
8. Chapter 6: Time Series and Forecasting 9. Chapter 7: Hypothesis Testing 10. Chapter 8: Model Complexity 11. Chapter 9: Function Decomposition 12. Chapter 10: Network Analysis 13. Part 3: Selected Advanced Concepts
14. Chapter 11: Dynamical Systems 15. Chapter 12: Kernel Methods 16. Chapter 13: Information Theory 17. Chapter 14: Non-Parametric Bayesian Methods 18. Chapter 15: Random Matrices 19. Index 20. Other Books You May Enjoy

Exercises

The following is a series of exercises. Answers to all the exercises are given in the Answers_to_Exercises_Chap7.ipynb Jupyter notebook in the GitHub repository:

  1. The Data/paired_sampled_ttest.csv file in the GitHub repository contains two columns of data corresponding to observations on paired samples. Use the scipy.stats.ttest_rel function from the SciPy package to run a two-tailed paired-sample t-test. Is the difference between the sample means statistically significant at the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:m="http://schemas.openxmlformats.org/officeDocument/2006/math"><mml:mi>α</mml:mi><mml:mo>=</mml:mo><mml:mn>0.05</mml:mn></mml:math> level?
  2. The object returned by the scipy.stats.ttest_rel function has a method that computes a confidence interval for the difference between the population means. Look at the documentation on scipy.stats.ttest_rel to see how to use this confidence interval method, and use it to calculate a 95% confidence interval for the paired sample in question 1.
  3. A paired sample test can also be thought of as a one-sample test performed on the differences between the paired observations. The data...
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