Jennifer, a college student, would like to make the claim that the average amount that students spend on textbooks each semester is more than $225. Jennifer samples 16 of her classmates and obtains a sample mean of $244. At the 2.5% significance level, should Jennifer reject or fail to reject the null hypothesis given the sample data below? • Ho : µ= $225; H : µ > $225 0.025 (significance level) • test statistic = 2.51 a = Use the graph below to select the type of test (left-, right, or two-tailed). Then set the a and the test statistic to determine the p-value. Use the results to determine whether to reject or fail to reject the null hypothesis. Move the blue dot to choose the appropriate test Significance level = 0.025 a=0.01 a=0.025 a=0.05 a=0.1 p-value = 0.834 test statistic = 0.97 196 to

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### Hypothesis Testing Visualization

#### Description:

This image features a standard normal distribution curve used for hypothesis testing. The x-axis represents the z-scores ranging from -4 to 4. 

- **Shaded Region:** Represents the p-value of 0.834, which indicates the probability of observing a test statistic as extreme as, or more extreme than, the observed value under the null hypothesis.
- **Vertical Line at z = -1.96:** Marks the critical value for a significance level (α) of 0.05 in a two-tailed test.
- **Test Statistic:** A red point indicates a test statistic value of 0.97 on the curve.
- **Significance Levels (α):** Four points at the top indicate different significance levels (α = 0.01, 0.025, 0.05, 0.1).

#### Question:

**Select the correct answer below:**

- ○ Do not reject the null hypothesis because the p-value 0.006 is less than the significance level α = 0.025.
- ○ **Reject the null hypothesis because the p-value 0.006 is less than the significance level α = 0.025.**
- ○ Reject the null hypothesis because 2.51 > 0.025.
- ○ Do not reject the null hypothesis because 2.51 > 0.025.
- ○ Reject the null hypothesis because the value of z is positive.
Transcribed Image Text:### Hypothesis Testing Visualization #### Description: This image features a standard normal distribution curve used for hypothesis testing. The x-axis represents the z-scores ranging from -4 to 4. - **Shaded Region:** Represents the p-value of 0.834, which indicates the probability of observing a test statistic as extreme as, or more extreme than, the observed value under the null hypothesis. - **Vertical Line at z = -1.96:** Marks the critical value for a significance level (α) of 0.05 in a two-tailed test. - **Test Statistic:** A red point indicates a test statistic value of 0.97 on the curve. - **Significance Levels (α):** Four points at the top indicate different significance levels (α = 0.01, 0.025, 0.05, 0.1). #### Question: **Select the correct answer below:** - ○ Do not reject the null hypothesis because the p-value 0.006 is less than the significance level α = 0.025. - ○ **Reject the null hypothesis because the p-value 0.006 is less than the significance level α = 0.025.** - ○ Reject the null hypothesis because 2.51 > 0.025. - ○ Do not reject the null hypothesis because 2.51 > 0.025. - ○ Reject the null hypothesis because the value of z is positive.
Jennifer, a college student, would like to make the claim that the average amount that students spend on textbooks each semester is more than $225. Jennifer samples 16 of her classmates and obtains a sample mean of $244.

At the 2.5% significance level, should Jennifer reject or fail to reject the null hypothesis given the sample data below?

- \( H_0: \mu = \$225; \, H_a: \mu > \$225 \)
- \( \alpha = 0.025 \) (significance level)
- test statistic = 2.51

Use the graph below to select the type of test (left-, right-, or two-tailed).

Then set the \(\alpha\) and the test statistic to determine the p-value. Use the results to determine whether to reject or fail to reject the null hypothesis.

---

**Graph Explanation:**

The graph displayed is a normal distribution curve used to visualize hypothesis testing.

- The x-axis represents the z-score, with markings from -4 to 4.
- Three small icons on the left allow the selection of a test type: left-tailed, right-tailed, and two-tailed.
- A blue dot on a slider can be moved vertically to choose the type of hypothesis test.
- The top of the graph includes a "Significance level = 0.025" label with additional \(\alpha\) levels (0.01, 0.05, 0.1) to choose from.
- The shaded region in the tail of the normal curve represents the p-value, which is displayed as 0.834.
- A red line at z = 0.97 illustrates the test statistic.

According to the graph, the p-value is 0.834, indicating the probability of observing the sample mean under the null hypothesis.
Transcribed Image Text:Jennifer, a college student, would like to make the claim that the average amount that students spend on textbooks each semester is more than $225. Jennifer samples 16 of her classmates and obtains a sample mean of $244. At the 2.5% significance level, should Jennifer reject or fail to reject the null hypothesis given the sample data below? - \( H_0: \mu = \$225; \, H_a: \mu > \$225 \) - \( \alpha = 0.025 \) (significance level) - test statistic = 2.51 Use the graph below to select the type of test (left-, right-, or two-tailed). Then set the \(\alpha\) and the test statistic to determine the p-value. Use the results to determine whether to reject or fail to reject the null hypothesis. --- **Graph Explanation:** The graph displayed is a normal distribution curve used to visualize hypothesis testing. - The x-axis represents the z-score, with markings from -4 to 4. - Three small icons on the left allow the selection of a test type: left-tailed, right-tailed, and two-tailed. - A blue dot on a slider can be moved vertically to choose the type of hypothesis test. - The top of the graph includes a "Significance level = 0.025" label with additional \(\alpha\) levels (0.01, 0.05, 0.1) to choose from. - The shaded region in the tail of the normal curve represents the p-value, which is displayed as 0.834. - A red line at z = 0.97 illustrates the test statistic. According to the graph, the p-value is 0.834, indicating the probability of observing the sample mean under the null hypothesis.
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