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 1.C.6
Textbook Question
Standard Deviation One way to get a very rough approximation of the value of a standard deviation of sample data is to find the range, then divide it by 4. The range is the difference between the highest sample value and the lowest sample value. In using this approach, what value is obtained from the sample data listed in Exercise 1 “IQ Scores�

1
Identify the highest and lowest values in the sample data set provided in Exercise 1 'IQ Scores'.
Calculate the range by subtracting the lowest value from the highest value in the sample data set.
Use the formula for the rough approximation of the standard deviation: divide the range by 4.
The result from the division gives a rough approximation of the standard deviation for the sample data.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Standard Deviation
Standard deviation is a measure of the amount of variation or dispersion in a set of values. It quantifies how much the values in a dataset deviate from the mean, providing insight into the spread of the data. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation suggests a wider range of values.
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Range
The range is a simple measure of variability in a dataset, calculated as the difference between the highest and lowest values. It provides a quick sense of the spread of the data but does not account for the distribution of values between the extremes. While useful for a rough estimate, it can be sensitive to outliers.
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Approximation Method for Standard Deviation
The approximation method for standard deviation involves dividing the range by 4 to estimate the standard deviation. This technique offers a quick, rough estimate, especially useful when detailed calculations are impractical. However, it assumes a normal distribution and may not be accurate for datasets with significant skewness or outliers.
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