Three randomly selected households are surveyed. The numbers of people in the households are 1, 4, and 10. Assume that samples of size n=2 are randomly selected with replacement from the population of 1, 4, and 10. Liste below are the nine different samples. Complete parts (a) through (c). 1,1 1,4 1,10 4,1 4,4 4,10 10,1 10,4 10,10 D a. Find the variance of each of the nine samples, then summarize the sampling distribution of the variances in the format of a table representing the probability distribution of the distinct variance values Probability (Type an integer or a fraction. Use ascending order of the sample variances.) b. Compare the population variance to the mean of the sample variances. Choose the correct answer below. O A. The population variance is equal to the square root of the mean of the sample variances. O B. The population variance is equal to the square of the mean of the sample variances. OC. The population variance is equal to the mean of the sample variances. c. Do the sample variances target the value of the population variance? In general, do sample variances make good estimators of population variances? Why or why not? Click to select your answer(S). Save for Later

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### Exercise on Variance and Sampling Distributions

#### Problem Statement
Three randomly selected households are surveyed. The numbers of people in the households are 1, 4, and 10. Assume that samples of size \( n = 2 \) are randomly selected with replacement from the population of 1, 4, and 10. Listed below are the nine different samples. Complete parts (a) through (c).

Samples:
- 1,1
- 1,4
- 1,10
- 4,1
- 4,4
- 4,10
- 10,1
- 10,4
- 10,10

#### Tasks

**a. Find the variance of each of the nine samples, then summarize the sampling distribution of the variances in the format of a table representing the probability distribution of the distinct variance values.**

\[
\begin{array}{c|c}
s^2 & \text{Probability} \\
\hline
 &  \\
 &  \\
 &  \\
 &  \\
 &  \\
\end{array}
\]
(Type an integer or a fraction. Use ascending order of the sample variances.)

**b. Compare the population variance to the mean of the sample variances. Choose the correct answer below.**
1. A. The population variance is equal to the square root of the mean of the sample variances.
2. B. The population variance is equal to the square of the mean of the sample variances.
3. C. The population variance is equal to the mean of the sample variances.

**c. Do the sample variances target the value of the population variance? In general, do sample variances make good estimators of population variances? Why or why not?**

(Click to select your answer.)

Save for Later
Transcribed Image Text:### Exercise on Variance and Sampling Distributions #### Problem Statement Three randomly selected households are surveyed. The numbers of people in the households are 1, 4, and 10. Assume that samples of size \( n = 2 \) are randomly selected with replacement from the population of 1, 4, and 10. Listed below are the nine different samples. Complete parts (a) through (c). Samples: - 1,1 - 1,4 - 1,10 - 4,1 - 4,4 - 4,10 - 10,1 - 10,4 - 10,10 #### Tasks **a. Find the variance of each of the nine samples, then summarize the sampling distribution of the variances in the format of a table representing the probability distribution of the distinct variance values.** \[ \begin{array}{c|c} s^2 & \text{Probability} \\ \hline & \\ & \\ & \\ & \\ & \\ \end{array} \] (Type an integer or a fraction. Use ascending order of the sample variances.) **b. Compare the population variance to the mean of the sample variances. Choose the correct answer below.** 1. A. The population variance is equal to the square root of the mean of the sample variances. 2. B. The population variance is equal to the square of the mean of the sample variances. 3. C. The population variance is equal to the mean of the sample variances. **c. Do the sample variances target the value of the population variance? In general, do sample variances make good estimators of population variances? Why or why not?** (Click to select your answer.) Save for Later
### Educational Content on Population Variance and Sample Variance Estimators

---

**c. Do the sample variances target the value of the population variance? In general, do sample variances make good estimators of population variances? Why or why not?**

Options:

- **A.** The sample variances do not target the population variance; therefore, sample variances do not make good estimators of population variances.
- **B.** The sample variances target the population variance; therefore, sample variances make good estimators of population variances.
- **C.** The sample variances do not target the population variance; therefore, sample variances make good estimators of population variances.
- **D.** The sample variances target the population variance; therefore, sample variances do not make good estimators of population variances.

**Click to select your answer(s).**

**Save for Later**

---

This content relates to the statistical concept of population variance and how well sample variance can estimate it. Generally, the goal is to determine whether sample variances can reliably reflect the actual population variance, providing a basis for making inferences about the larger population from a subset sample.

In practice:

- **Sample Variance** (\( s^2 \)) is calculated from a sample and used to estimate the population variance.
- **Population Variance** (\( \sigma^2 \)) is the true variance within the entire population.

Choosing the correct option will depend on understanding the principles behind unbiased and biased estimators in statistics. An unbiased estimator means that the expected value of the estimator equals the parameter it estimates, which, in many standard cases, applies to the sample variance as a good estimator of the population variance.
Transcribed Image Text:### Educational Content on Population Variance and Sample Variance Estimators --- **c. Do the sample variances target the value of the population variance? In general, do sample variances make good estimators of population variances? Why or why not?** Options: - **A.** The sample variances do not target the population variance; therefore, sample variances do not make good estimators of population variances. - **B.** The sample variances target the population variance; therefore, sample variances make good estimators of population variances. - **C.** The sample variances do not target the population variance; therefore, sample variances make good estimators of population variances. - **D.** The sample variances target the population variance; therefore, sample variances do not make good estimators of population variances. **Click to select your answer(s).** **Save for Later** --- This content relates to the statistical concept of population variance and how well sample variance can estimate it. Generally, the goal is to determine whether sample variances can reliably reflect the actual population variance, providing a basis for making inferences about the larger population from a subset sample. In practice: - **Sample Variance** (\( s^2 \)) is calculated from a sample and used to estimate the population variance. - **Population Variance** (\( \sigma^2 \)) is the true variance within the entire population. Choosing the correct option will depend on understanding the principles behind unbiased and biased estimators in statistics. An unbiased estimator means that the expected value of the estimator equals the parameter it estimates, which, in many standard cases, applies to the sample variance as a good estimator of the population variance.
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