Moviegoers The average "moviegoer" sees 8.5 movies a year. A moviegoer is defined as a person who sees at least one movie in a theater in a 12-month period. A random sample of 42 moviegoers from a large university revealed that the average number of movies seen per person was 10.2. The population standard deviation is 3.2 movies. At the 0.01 level of significance, can it be concluded that this represents a difference from the national average? Part 1 of 5 State the hypotheses and identify the claim with the correct hypothesis. Hoμ = 8.5 not claim ▼ H₁μ8.5 claim This hypothesis test is a two-tailed Part: 1/5 Part 2 of 5 test. Find the critical value(s). Round the answer to at least two decimal places. If there is more than one critical value, separate them with commas. Critical value(s): X 8 民圆口心园 ✪

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**Title: Understanding Hypothesis Testing in Movie-Going Habits**

**Introduction:**
This educational content explores a hypothesis test concerning the average number of movies watched by moviegoers. A moviegoer is defined as someone who watches at least one movie in a theater over a 12-month period. We examine whether a sample mean differs significantly from a known national average.

**Problem Statement:**
The average moviegoer sees 8.5 movies per year. A sample of 42 moviegoers from a large university reported an average of 10.2 movies per year. Given a population standard deviation of 3.2 movies, we will perform a hypothesis test at the 0.01 level of significance to determine if this difference is significant.

**Part 1 of 5: Stating the Hypotheses**

1. **Null Hypothesis (H₀):** μ = 8.5; the average number of movies watched is 8.5.
2. **Alternative Hypothesis (H₁):** μ ≠ 8.5; the average number of movies watched is not 8.5.

This scenario requires a two-tailed test, which checks if the sample mean is significantly different, either higher or lower, than the population mean.

**Part 2 of 5: Critical Values**

- To find the critical value(s), calculations must be rounded to at least two decimal places. Should there be multiple critical values, they should be separated by commas.

**Note on Graphs/Diagrams:**
- This segment does not include specific graphs or diagrams. However, in a typical educational setting, Z-distribution tables or graphs illustrating the two-tailed hypothesis test would be helpful in visualizing the critical regions.

This educational example guides students in understanding the process of hypothesis testing using real-world data and statistical reasoning.
Transcribed Image Text:**Title: Understanding Hypothesis Testing in Movie-Going Habits** **Introduction:** This educational content explores a hypothesis test concerning the average number of movies watched by moviegoers. A moviegoer is defined as someone who watches at least one movie in a theater over a 12-month period. We examine whether a sample mean differs significantly from a known national average. **Problem Statement:** The average moviegoer sees 8.5 movies per year. A sample of 42 moviegoers from a large university reported an average of 10.2 movies per year. Given a population standard deviation of 3.2 movies, we will perform a hypothesis test at the 0.01 level of significance to determine if this difference is significant. **Part 1 of 5: Stating the Hypotheses** 1. **Null Hypothesis (H₀):** μ = 8.5; the average number of movies watched is 8.5. 2. **Alternative Hypothesis (H₁):** μ ≠ 8.5; the average number of movies watched is not 8.5. This scenario requires a two-tailed test, which checks if the sample mean is significantly different, either higher or lower, than the population mean. **Part 2 of 5: Critical Values** - To find the critical value(s), calculations must be rounded to at least two decimal places. Should there be multiple critical values, they should be separated by commas. **Note on Graphs/Diagrams:** - This segment does not include specific graphs or diagrams. However, in a typical educational setting, Z-distribution tables or graphs illustrating the two-tailed hypothesis test would be helpful in visualizing the critical regions. This educational example guides students in understanding the process of hypothesis testing using real-world data and statistical reasoning.
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