Python for Introductory Statistics
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Simon Aman, City Colleges of Chicago
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Publisher: City Colleges of Chicago
Language: English
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CC BY
Table of Contents
- Why Learn Python?
- 1. Introduction to Python
- 2. Python Lists
- 3. Python Syntax
- 4. Python Loops
- 5. Frequency Distributions and Graphs
- 6. Measures of Center and Speed
- 7. Measures of Position
- 8. Discrete Probability Distributions
- 9. Continuous Probability Distributions
- 10. Confidence Intervals
- 11. Hypothesis Testing
- 12. Linear Regression and Correlation
- 13. Analysis of Categorical Data
- 14. Advanced Topics
- Appendix 1: Python Installation
- Appendix 2: Random Integer Generator
- Appendix 3: Factorial
- Code References
- Resources Links
About the Book
The purpose of this material is to provide an overview of the free programming language, Python, and a few of its software libraries that are most useful for improving Introductory Statistics students' learning and for providing an alternative statistical software package for those who perform statistical data analysis and plotting. This material, along with the companion workbook and a free web-based Python platform, could easily replace the use of other software packages and calculators in an Introductory Statistics course. Part I, Sections 1 to 4, covers the basics of the Python programming language. Part II, Sections 5 to 13, focuses on Python for introductory statistics, and Part III, Section 14, covers selected advanced statistics topics in Python. Additionally, there are demo video links accompanying key steps for further instruction. No prior programming knowledge is required or assumed.
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All images and equations have been checked for accessibility, especially the PDF version.
About the Contributors
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Simon Aman, City Colleges of Chicago