Are job applicants with easy to pronounce last names just as likely to get called for an interview than applicants with difficult to pronounce last names. 633 job applications were sent out with last names that are easy to pronounce and 703 identical job applications were sent out with names that were difficult to pronounce. 484 of the "applicants" with easy to pronounce names were called for an interview while 562 of the "applicants" with difficult to pronounce names were called for an interview. What can be concluded at the 0.10 level of significance? For this study, we should use Select an answer a. The null and alternative hypotheses would be: He: Select an answer H₁: Select an answer Select an answer Select an answer Select an answer Select an answer (please enter a decimal) (Please enter a decimal) b. The test statistic c. The p-value = d. The p-value is [ e. Based on this, we should [Select an answer the null hypothesis. f. Thus, the final conclusion is that... (please show your answer to 3 decimal places.) (Please show your answer to 4 decimal places.) The results are statistically significant at x = 0.10, so there is sufficient evidence to conclude that the proportion of the 633 applicants with easy to pronounce names who got called for an interview is not the same as the proportion of the 703 applicants with difficult to pronounce names who got called for an interview. O The results are statistically insignificant at x = 0.10, so we can conclude that the population proportion of people with easy to pronounce names who get called for an interview is equal to the population proportion of people with difficult to pronounce names who get called for an interview. The results are statistically insignificant at a = 0.10, so there is insufficient evidence to conclude that among all possible applicants, there is a differnece in the population proportion of callbacks for applicants with easy to pronounce last names and applicants with difficult to pronounce names. The results are statistically significant at a=0.10, so there is sufficient evidence to conclude that among all possible applicants, there is a differnece in the population proportion of callbacks for applicants with easy to pronounce last names and applicants with difficult to pronounce names. g. Interpret the p-value in the context of the study. O There is a 12.32% chance of a Type I error. There is a 12.32% chance that percent of callbacks for applicants with easy to pronounce names and those with difficult to pronounce names differ by at least 3.5%. If the sample proportion of applicants with easy to pronounce names who receive a callback is the same as the sample proportion of applicants with difficult to pronounce names who receive a callback and if another another 633 applications with easy to pronounce names and 703 applications with difficult to pronounce names are submitted then there would be a 12.32% chance of concluding that the percent callbacks for applicants with easy to pronounce names and applicants with difficult to pronounce names differ by at least 3.5%. O If the population proportion of callbacks for applicants with easy to pronounce last names is the same as the population proportion of callbacks for applicants with difficult to pronounce last names and if another 633 applications with easy to pronounce names and 703 applications with difficult to pronounce names are submitted then there would be a 12.32% chance that the percent of callbacks for the sample of applicants with easy to pronounce names and the percent of callbacks for the sample of applicants with difficult to pronounce names would differ by at least 3.5%. h. Interpret the level of significance in the context of the study. There is a 10% chance that the manager's son will get the job, so it is pointless to apply no matter what your last name is. If the population proportion of callbacks for applicants with easy to pronounce last names is the same as the population proportion of callbacks for applicants with difficult to pronounce last names and if another 633 applications with easy to pronounce names and 703 applications with difficult to pronounce names are submitted then there would be a 10% chance that we would end up falsely concuding that the proportion of callbacks for the submitted applications with easy to pronounce last names is different from the proportion of callbacks for the submitted applications with difficult to pronounce last names. O If the population proportion of callbacks for applicants with easy to pronounce last names is the same as the population proportion of callbacks for applicants with difficult to pronounce last names and if another 633 applications with easy to pronounce names and 703 applications with difficult to pronounce names are submitted then there would be a 10% chance that we would end up falsely concuding that the population proportion of callbacks for applicants with easy to pronounce last names is different from the population proportion of callbacks for applicants with difficult to pronounce last names.

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**Educational Resource Transcription on Statistical Analysis**

**Context:**
The study investigates whether job applicants with easy-to-pronounce last names are just as likely to be called for an interview as those with difficult-to-pronounce last names. A total of 633 applications were sent with easy names, and 703 with difficult names. 484 candidates with easy names and 562 with difficult names were called for interviews. The analysis is conducted at a 0.10 level of significance.

**Hypotheses:**

- Null hypothesis \( H_0 \): No difference in the proportion of callbacks for easy and difficult names.
- Alternative hypothesis \( H_1 \): There is a difference in the proportion of callbacks.

**Statistical Analysis:**

a. **Test Statistic:**
- The z-value should be calculated up to three decimal places.

b. **Critical Value:**
- Determine and display the critical value up to four decimal places.

c. **P-value:**
- Compare the p-value with the significance level (\( \alpha = 0.10 \)).

d. **Decision Rule:**
- Based on the above calculations, decide whether to reject or fail to reject \( H_0 \).

e. **Conclusion:**
- Determine whether the difference in callback rates is statistically significant.

**Interpretations:**

g. **P-value Interpretation:**
- Understanding the p-value in the study's context, including the probability difference and Type I error.

h. **Significance Level Interpretation:**
- Evaluation of the practical impact of applying with a particular last name.

**Multiple Choice Answers:**
- The options provided cover scenarios from statistical significance to practical implications regarding the pronunciation of last names in job applications.

This educational resource aims to guide learners through understanding statistical hypothesis testing and its implications in real-world scenarios, using a focused example on employment discrimination based on name pronunciation.
Transcribed Image Text:**Educational Resource Transcription on Statistical Analysis** **Context:** The study investigates whether job applicants with easy-to-pronounce last names are just as likely to be called for an interview as those with difficult-to-pronounce last names. A total of 633 applications were sent with easy names, and 703 with difficult names. 484 candidates with easy names and 562 with difficult names were called for interviews. The analysis is conducted at a 0.10 level of significance. **Hypotheses:** - Null hypothesis \( H_0 \): No difference in the proportion of callbacks for easy and difficult names. - Alternative hypothesis \( H_1 \): There is a difference in the proportion of callbacks. **Statistical Analysis:** a. **Test Statistic:** - The z-value should be calculated up to three decimal places. b. **Critical Value:** - Determine and display the critical value up to four decimal places. c. **P-value:** - Compare the p-value with the significance level (\( \alpha = 0.10 \)). d. **Decision Rule:** - Based on the above calculations, decide whether to reject or fail to reject \( H_0 \). e. **Conclusion:** - Determine whether the difference in callback rates is statistically significant. **Interpretations:** g. **P-value Interpretation:** - Understanding the p-value in the study's context, including the probability difference and Type I error. h. **Significance Level Interpretation:** - Evaluation of the practical impact of applying with a particular last name. **Multiple Choice Answers:** - The options provided cover scenarios from statistical significance to practical implications regarding the pronunciation of last names in job applications. This educational resource aims to guide learners through understanding statistical hypothesis testing and its implications in real-world scenarios, using a focused example on employment discrimination based on name pronunciation.
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