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
3. Describing Data Numerically
Standard Deviation
Problem 2.4.48
Textbook Question
Comparing Variation in Different Data Sets In Exercises 45–50, find the coefficient of variation for each of the two data sets. Then compare the results.
Heights and Weights The heights (in inches) and weights (in pounds) of every France national soccer team player that started the 2018 FIFA Men’s World Cup final are listed. (Source: ESPN)


1
Step 1: Understand the coefficient of variation (CV). The CV is a measure of relative variability and is calculated as the ratio of the standard deviation (SD) to the mean (μ), expressed as a percentage: CV = (SD / μ) × 100.
Step 2: Calculate the mean (μ) for each data set. For the heights, sum all the values and divide by the number of players. Repeat the same process for the weights.
Step 3: Calculate the standard deviation (SD) for each data set. Use the formula: SD = sqrt(Σ(xi - μ)^2 / n), where xi represents each individual value, μ is the mean, and n is the number of values in the data set.
Step 4: Compute the coefficient of variation (CV) for each data set using the formula CV = (SD / μ) × 100. Perform this calculation separately for the heights and weights.
Step 5: Compare the CVs of the two data sets. A higher CV indicates greater relative variability in the data set. Discuss the implications of the comparison in terms of the variability of heights versus weights.

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