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📚 Python for Introductory Statistics
Chapters ▾
0. Why Learn Python?1. Introduction to Python2. Python Lists3. Python Syntax4. Python Loops5. Frequency Distributions and Graphs6. Measures of Center and Variation7. Measures of Position8. Discrete Probability Distributions9. Continuous Probability Distributions10. Confidence Intervals11. Hypothesis Testing12. Linear Regression and Correlation13. Analysis of Categorical Data14. Advanced Statistics TopicsAppendix 1: Python Installing StepsAppendix 2: Random Integer GeneratorAppendix 3: Counting, Permutations and CombinationsCode ReferencesResources

12. Linear Regression and Correlation

How do we measure a relationship between two quantitative variables? For example, what is the relationship between students’ time spent studying for a test and their test scores? In general, the more time spent studying (more hours) would yield a higher test score. There is a direct or positive relationship between time spent and test scores. But how strong is the relationship?

Another example is the relationship between the age (years) of a car and its price (in dollars). In general, the older the car (more years) the cheaper (less dollars) it costs. The relationship is indirect or negative. What type and how strong is the relationship?

Adapted from Python for Introductory Statistics, by Simon Aman (Truman College, City Colleges of Chicago), licensed under CC BY 4.0. Changes were made: reformatted as an accessible XYZ web edition with live in-browser code cells. License: CC-BY-4.0.