Listed below are the top 10 annual salaries (in millions of dollars) of TV personalities. Find the range, variance, and standard deviation for the sample data. Given that these are the top 10 salaries, do we know anything about the variation of salaries of TV personalities in general? 38 36 35 29 18 15 13 12 11.5 10.9 D The range of the sample data is S million. (Type an integer or a decimal.) The variance of the sample data is (Round to two decimal places as needed.) The standard deviation of the sample data is Smillion. (Round to two decimal places as needed.) Is the standard deviation of the sample a good estimate of the variation of salaries of TV personalities in general? O A. No, because the sample is not representative of the whole population. O B. Yes, because the sample is random. O C. Yes, because the standard deviation is an unbiased estimator. O D. No, because there is an outlier in the sample data.

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**Educational Content on Sample Data Analysis**

**Introduction**

This lesson explores the concepts of range, variance, and standard deviation using a sample data set: the top 10 annual salaries (in millions of dollars) of TV personalities. By calculating these statistical measures, we aim to understand the variation in salaries among top TV personalities.

**Sample Data:**

- Salaries (in millions): 38, 36, 35, 29, 18, 15, 13, 12, 11.5, 10.9

**Tasks:**

1. **Calculate the Range:**
   - The range is the difference between the highest and lowest values in a data set.
   - **Formula:** Range = Maximum value - Minimum value

2. **Calculate the Variance:**
   - Variance measures the spread of the data points around the mean.
   - **Formula:** Variance = Σ (xi - mean)² / (n - 1), where n is the number of observations.

3. **Calculate the Standard Deviation:**
   - Standard Deviation is the square root of the variance, providing a measure of the average distance from the mean.
   - **Formula:** Standard Deviation = √Variance

4. **Interpretation:**
   - Determine if the standard deviation of the sample is a good estimate for the variation of salaries of TV personalities in general.
   
**Questions for Consideration:**

- Is the standard deviation of the sample a good estimate of the variation of salaries of TV personalities in general?
  - A. No, because the sample is not representative of the whole population.
  - B. Yes, because the sample is random.
  - C. Yes, because the standard deviation is an unbiased estimator.
  - D. No, because there is an outlier in the sample data.

By analyzing the calculated statistical values and evaluating the nature of the sample, students will better understand how these concepts apply to real-world data and the limitations of using sample data to make generalizations.
Transcribed Image Text:**Educational Content on Sample Data Analysis** **Introduction** This lesson explores the concepts of range, variance, and standard deviation using a sample data set: the top 10 annual salaries (in millions of dollars) of TV personalities. By calculating these statistical measures, we aim to understand the variation in salaries among top TV personalities. **Sample Data:** - Salaries (in millions): 38, 36, 35, 29, 18, 15, 13, 12, 11.5, 10.9 **Tasks:** 1. **Calculate the Range:** - The range is the difference between the highest and lowest values in a data set. - **Formula:** Range = Maximum value - Minimum value 2. **Calculate the Variance:** - Variance measures the spread of the data points around the mean. - **Formula:** Variance = Σ (xi - mean)² / (n - 1), where n is the number of observations. 3. **Calculate the Standard Deviation:** - Standard Deviation is the square root of the variance, providing a measure of the average distance from the mean. - **Formula:** Standard Deviation = √Variance 4. **Interpretation:** - Determine if the standard deviation of the sample is a good estimate for the variation of salaries of TV personalities in general. **Questions for Consideration:** - Is the standard deviation of the sample a good estimate of the variation of salaries of TV personalities in general? - A. No, because the sample is not representative of the whole population. - B. Yes, because the sample is random. - C. Yes, because the standard deviation is an unbiased estimator. - D. No, because there is an outlier in the sample data. By analyzing the calculated statistical values and evaluating the nature of the sample, students will better understand how these concepts apply to real-world data and the limitations of using sample data to make generalizations.
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