Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
1. Intro to Stats and Collecting Data
Intro to Stats
Problem 10.1.1c
Textbook Question
Notation The author conducted an experiment in which the height of each student was measured in centimeters and those heights were matched with the same students’ scores on the first statistics test.
c. Does r change if the heights are converted from centimeters to inches?

1
Understand that 'r' refers to the correlation coefficient, which measures the strength and direction of a linear relationship between two variables.
Recall that the correlation coefficient 'r' is a dimensionless quantity, meaning it does not depend on the units of measurement of the variables involved.
Recognize that converting the heights from centimeters to inches is a linear transformation, which involves multiplying each height by a constant factor (1 inch = 2.54 cm).
Note that linear transformations of the form y = ax + b, where a and b are constants, do not affect the correlation coefficient 'r'.
Conclude that since the conversion from centimeters to inches is a linear transformation, the value of 'r' remains unchanged.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Correlation Coefficient (r)
The correlation coefficient, denoted as 'r', measures the strength and direction of a linear relationship between two variables. It ranges from -1 to 1, where values close to 1 or -1 indicate strong relationships, and values near 0 suggest weak or no linear relationship. It is unaffected by changes in the units of measurement of the variables.
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Correlation Coefficient
Unit Conversion
Unit conversion involves changing the measurement units of a variable, such as converting heights from centimeters to inches. While this alters the numerical values of the data, it does not affect the relative positions or the relationship between the variables, meaning the correlation coefficient remains unchanged.
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Step 1: Write Hypotheses
Scale Invariance
Scale invariance refers to the property of a statistical measure that remains unchanged when the scale of measurement is altered. The correlation coefficient is scale invariant, meaning that converting units of measurement, such as from centimeters to inches, does not affect the value of 'r', as it depends only on the relative positions of the data points.
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