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.
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.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
need help please!
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 7 steps with 7 images
Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman