The ages of a group of 158 randomly selected adult females have a standard deviation of 18.9 years. Assume that the ages of female statistics students have less variation than ages of females in the general population, so let o= 18.9 years for the sample size calculation. How many female statistics student ages must be obtained in order to estimate the mean age of all female statistics students? Assume that we want 98% confidence that the sample mean is within one-half year of the population mean. Does it seem reasonable to assume that the ages of female statistics students have less variation than ages of females in the general population? The required sample size is (Round up to the nearest whole number as needed.) Does it seem reasonable to assume that the ages of female statistics students have less variation than ages of females in the general population? O A. Yes, because statistics students are typically younger than people in the general population. O B. No, because statistics students are typically older than people in the general population. O C. No, because there is no age difference between the population of statistics students and the general population. O D. Yes, because statistics students are typically older than people in the general population.

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### Understanding the Sample Size Calculation for Female Statistics Students' Ages

In this exercise, we explore the task of estimating the mean age of all female statistics students. A sample of 158 randomly selected adult females shows a standard deviation of 18.9 years. It’s assumed that the ages of female statistics students have less variation than those in the general population. We aim to find out the required sample size to achieve a 98% confidence level that the sample mean is accurate within one-half year of the population mean.

**Sample Size Requirement:**
- **Round up to the nearest whole number** to determine the necessary sample size.

**Question:**
Does it seem reasonable to assume that the ages of female statistics students have less variation than the ages of females in the general population?

**Options:**
- **A.** Yes, because statistics students are typically younger than people in the general population.
- **B.** No, because statistics students are typically older than people in the general population.
- **C.** No, because there is no age difference between the population of statistics students and the general population.
- **D.** Yes, because statistics students are typically older than people in the general population.

This example highlights important statistical concepts such as sample size determination, standard deviation, and confidence intervals, which are crucial for conducting accurate and reliable statistical analyses.
Transcribed Image Text:### Understanding the Sample Size Calculation for Female Statistics Students' Ages In this exercise, we explore the task of estimating the mean age of all female statistics students. A sample of 158 randomly selected adult females shows a standard deviation of 18.9 years. It’s assumed that the ages of female statistics students have less variation than those in the general population. We aim to find out the required sample size to achieve a 98% confidence level that the sample mean is accurate within one-half year of the population mean. **Sample Size Requirement:** - **Round up to the nearest whole number** to determine the necessary sample size. **Question:** Does it seem reasonable to assume that the ages of female statistics students have less variation than the ages of females in the general population? **Options:** - **A.** Yes, because statistics students are typically younger than people in the general population. - **B.** No, because statistics students are typically older than people in the general population. - **C.** No, because there is no age difference between the population of statistics students and the general population. - **D.** Yes, because statistics students are typically older than people in the general population. This example highlights important statistical concepts such as sample size determination, standard deviation, and confidence intervals, which are crucial for conducting accurate and reliable statistical analyses.
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