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Are job applicants with easy to pronounce last names more likely to get called for an interview than applicants with difficult to pronounce last names. 607 job applications were sent out with last names that are easy to pronounce and 759 identical job applications were sent out with names that were difficult to pronounce. 378 of the "applicants" with easy to pronounce names were called for an interview while 456 of the "applicants" with difficult to pronounce names were called for an interview. What can be concluded at the 0.05 level of significance? For this study, we should use Select an answer a. The null and alternative hypotheses would be: Ho Select an answer V Select an answer V Select an answer v (please enter a decimal) H: Select an answer v Select an answer v Select an answer v (Please enter a decimal) b. The test statistic ?v (please show your answer to 3 decimal places.) C. The p-value = (Please show your answer to 4 decimal places.)

Are job applicants with easy to pronounce last names more likely to get called for an interview than applicants with difficult to pronounce last names. 607 job applications were sent out with last names that are easy to pronounce and 759 identical job applications were sent out with names that were difficult to pronounce. 378 of the "applicants" with easy to pronounce names were called for an interview while 456 of the "applicants" with difficult to pronounce names were called for an interview. What can be concluded at the 0.05 level of significance? For this study, we should use Select an answer a. The null and alternative hypotheses would be: Ho Select an answer V Select an answer V Select an answer v (please enter a decimal) H: Select an answer v Select an answer v Select an answer v (Please enter a decimal) b. The test statistic ?v (please show your answer to 3 decimal places.) C. The p-value = (Please show your answer to 4 decimal places.)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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### Understanding Name Pronunciation Bias in Job Interviews **Research Question** Are job applicants with easy-to-pronounce last names more likely to receive an interview than those with difficult-to-pronounce last names? A study was conducted to explore this question, with 607 applications sent out with easy-to-pronounce names and 759 with difficult-to-pronounce names. Of these, 378 applicants with easy names and 456 with difficult names were called for an interview. The aim is to determine if there's a significant difference at the 0.05 level. **Study Design** For this study, a hypothesis test should be conducted using the following steps: #### a. Formulating Hypotheses - **Null Hypothesis (\(H_0\))**: There is no difference in the likelihood of getting an interview between easy-to-pronounce and difficult-to-pronounce last names. - **Alternative Hypothesis (\(H_1\))**: There is a significant difference in the likelihood of getting an interview between easy-to-pronounce and difficult-to-pronounce last names. #### b. Calculating the Test Statistic Calculate the test statistic to three decimal places to evaluate the hypotheses. #### c. Determining the p-value Calculate the p-value to four decimal places to assess the strength of the evidence against the null hypothesis. #### e. Conclusion Base the decision on whether the p-value is less than or greater than the significance level (\(\alpha = 0.05\)): - If \(p \leq \alpha\), reject the null hypothesis. - If \(p > \alpha\), fail to reject the null hypothesis. Evaluate the results to determine if the null hypothesis should be rejected, indicating a bias based on name pronunciation in hiring practices.
Transcribed Image Text:### Understanding Name Pronunciation Bias in Job Interviews **Research Question** Are job applicants with easy-to-pronounce last names more likely to receive an interview than those with difficult-to-pronounce last names? A study was conducted to explore this question, with 607 applications sent out with easy-to-pronounce names and 759 with difficult-to-pronounce names. Of these, 378 applicants with easy names and 456 with difficult names were called for an interview. The aim is to determine if there's a significant difference at the 0.05 level. **Study Design** For this study, a hypothesis test should be conducted using the following steps: #### a. Formulating Hypotheses - **Null Hypothesis (\(H_0\))**: There is no difference in the likelihood of getting an interview between easy-to-pronounce and difficult-to-pronounce last names. - **Alternative Hypothesis (\(H_1\))**: There is a significant difference in the likelihood of getting an interview between easy-to-pronounce and difficult-to-pronounce last names. #### b. Calculating the Test Statistic Calculate the test statistic to three decimal places to evaluate the hypotheses. #### c. Determining the p-value Calculate the p-value to four decimal places to assess the strength of the evidence against the null hypothesis. #### e. Conclusion Base the decision on whether the p-value is less than or greater than the significance level (\(\alpha = 0.05\)): - If \(p \leq \alpha\), reject the null hypothesis. - If \(p > \alpha\), fail to reject the null hypothesis. Evaluate the results to determine if the null hypothesis should be rejected, indicating a bias based on name pronunciation in hiring practices.
f. Thus, the final conclusion is that: - ○ The results are statistically insignificant at α = 0.05, so there is insufficient evidence to conclude that applicants with easy to pronounce last names are more likely to get called for an interview compared to applicants with difficult to pronounce last names. - ○ The results are statistically significant at α = 0.05, so there is sufficient evidence to conclude that the proportion of the 607 applicants with easy to pronounce names who got called for an interview is greater than the proportion of the 759 applicants with difficult to pronounce names who got called for an interview. - ○ The results are statistically significant at α = 0.05, so there is sufficient evidence to conclude that among all possible applicants, people with easy to pronounce last names are more likely to get called for an interview compared to people with difficult to pronounce last names. - ○ The results are statistically insignificant at α = 0.05, so we can conclude that the population proportion of applicants with easy to pronounce names who get called for an interview is equal to the population proportion of applicants with difficult to pronounce names who get called for an interview. g. Interpret the p-value in the context of the study. - ○ 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 607 applications with easy to pronounce names and 759 applications with difficult to pronounce names are submitted then there would be a 20.43% chance that the percent of callbacks for the sample of applicants with easy to pronounce names would be at least 2.2% more than the percent of callbacks for applicants with difficult to pronounce names. - ○ There is a 20.43% chance that applicants with easy to pronounce names are 2.2% more likely to receive a callback than applicants with difficult to pronounce names. - ○ There is a 20.43% chance of a Type I error. - ○ 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 607 applications with easy to pronounce names and 759 applications with difficult to pronounce names are submitted then there would be a 20.43% chance of concluding that applicants with easy to pronounce names are at least 2.2% more likely to receive a callback than applicants with difficult to
Transcribed Image Text:f. Thus, the final conclusion is that: - ○ The results are statistically insignificant at α = 0.05, so there is insufficient evidence to conclude that applicants with easy to pronounce last names are more likely to get called for an interview compared to applicants with difficult to pronounce last names. - ○ The results are statistically significant at α = 0.05, so there is sufficient evidence to conclude that the proportion of the 607 applicants with easy to pronounce names who got called for an interview is greater than the proportion of the 759 applicants with difficult to pronounce names who got called for an interview. - ○ The results are statistically significant at α = 0.05, so there is sufficient evidence to conclude that among all possible applicants, people with easy to pronounce last names are more likely to get called for an interview compared to people with difficult to pronounce last names. - ○ The results are statistically insignificant at α = 0.05, so we can conclude that the population proportion of applicants with easy to pronounce names who get called for an interview is equal to the population proportion of applicants with difficult to pronounce names who get called for an interview. g. Interpret the p-value in the context of the study. - ○ 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 607 applications with easy to pronounce names and 759 applications with difficult to pronounce names are submitted then there would be a 20.43% chance that the percent of callbacks for the sample of applicants with easy to pronounce names would be at least 2.2% more than the percent of callbacks for applicants with difficult to pronounce names. - ○ There is a 20.43% chance that applicants with easy to pronounce names are 2.2% more likely to receive a callback than applicants with difficult to pronounce names. - ○ There is a 20.43% chance of a Type I error. - ○ 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 607 applications with easy to pronounce names and 759 applications with difficult to pronounce names are submitted then there would be a 20.43% chance of concluding that applicants with easy to pronounce names are at least 2.2% more likely to receive a callback than applicants with difficult to
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