A report states that the mean yearly salary offer for students graduating with a degree in account is $48,722. Suppose that a random sample of 50 accounting graduates at a large university who received job offers resulted in a mean offer of $49,870 and a standard deviation of $3900. Do the sample data provide strong support for the claim that the mean salary offer for accounting graduates of this university is higher than the national average of $48,722? Hoi µ = Ha: H Select an answer v |(Put in the correct symbol and value) a = P-value = Based on the above we choose to Select an answer

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Chapter10: Statistics
Section10.4: Distributions Of Data
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### Hypothesis Testing for Mean Salary Offer for Accounting Graduates

A report states that the mean yearly salary offer for students graduating with a degree in accounting is $48,722. Suppose that a random sample of 50 accounting graduates at a large university who received job offers resulted in a mean offer of $49,870 and a standard deviation of $3900. Do the sample data provide strong support for the claim that the mean salary offer for accounting graduates of this university is higher than the national average of $48,722?

#### Hypotheses

Let's define our null and alternative hypotheses:

- **Null Hypothesis (H0):** The mean salary offer for accounting graduates from the university (\(\mu\)) is equal to the national average ($48,722).
\[
H_0: \mu = 48722
\]
- **Alternative Hypothesis (Ha):** The mean salary offer for accounting graduates from the university (\(\mu\)) is higher than the national average ($48,722).
\[
H_a: \mu > 48722
\]

#### Significance Level (α)

Typically, the significance level (α) will be set before conducting the test and commonly used values are 0.05, 0.01, or 0.10.

\[
\alpha = \_\_\_\_
\]

#### P-value Calculation

The p-value helps us determine the significance of our results. Generally, statistical software or tables are used to find this value based on the test statistic calculated from the sample data.

\[
\text{P-value} = \_\_\_\_
\]

#### Conclusion

Based on the p-value and the selected significance level (α), we decide whether to reject the null hypothesis.

\[
\text{Based on the above, we choose to} \_\_\_\_\_\_\_\_\_\_
\]

_Please fill in the blanks with the correct symbol and value for Ha, the chosen significance level, and the calculated p-value. Select the appropriate decision (reject or fail to reject the null hypothesis) based on your comparison of the p-value and significance level._

#### Additional Explanation:

If a diagram or graph was provided, we'd explain it here, detailing what each axis represents, what the data trends show, etc. However, in this case, there are no graphs or diagrams to elaborate on.
Transcribed Image Text:### Hypothesis Testing for Mean Salary Offer for Accounting Graduates A report states that the mean yearly salary offer for students graduating with a degree in accounting is $48,722. Suppose that a random sample of 50 accounting graduates at a large university who received job offers resulted in a mean offer of $49,870 and a standard deviation of $3900. Do the sample data provide strong support for the claim that the mean salary offer for accounting graduates of this university is higher than the national average of $48,722? #### Hypotheses Let's define our null and alternative hypotheses: - **Null Hypothesis (H0):** The mean salary offer for accounting graduates from the university (\(\mu\)) is equal to the national average ($48,722). \[ H_0: \mu = 48722 \] - **Alternative Hypothesis (Ha):** The mean salary offer for accounting graduates from the university (\(\mu\)) is higher than the national average ($48,722). \[ H_a: \mu > 48722 \] #### Significance Level (α) Typically, the significance level (α) will be set before conducting the test and commonly used values are 0.05, 0.01, or 0.10. \[ \alpha = \_\_\_\_ \] #### P-value Calculation The p-value helps us determine the significance of our results. Generally, statistical software or tables are used to find this value based on the test statistic calculated from the sample data. \[ \text{P-value} = \_\_\_\_ \] #### Conclusion Based on the p-value and the selected significance level (α), we decide whether to reject the null hypothesis. \[ \text{Based on the above, we choose to} \_\_\_\_\_\_\_\_\_\_ \] _Please fill in the blanks with the correct symbol and value for Ha, the chosen significance level, and the calculated p-value. Select the appropriate decision (reject or fail to reject the null hypothesis) based on your comparison of the p-value and significance level._ #### Additional Explanation: If a diagram or graph was provided, we'd explain it here, detailing what each axis represents, what the data trends show, etc. However, in this case, there are no graphs or diagrams to elaborate on.
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