You are looking for a way to incentivize the sales reps that you are in charge of. Youdesign an incentive plan as a way to help increase in their sales. To evaluate thisinnovative plan, you take a random sample of your reps, and their weekly incomesbefore and after the plan were recorded. You calculate the difference in income as(after incentive plan - before incentive plan). You perform a paired samples t-testwith the following hypotheses: Null Hypothesis: HD = 0, Alternative Hypothesis: HD =O. You calculate a p-value of 0.8297. What is the appropriate conclusion of your test?%3DO 1)The average difference in weekly income is significantly different from 0.There is a significant difference in weekly income due to the incentive plan.We did not find enough evidence to say there was a significantly negativeO 2)average difference in weekly income. The incentive plan does not appear tohave been effective.O 3) We did not find enough evidence to say the average difference in weekly3)income was not 0. The incentive plan does not appear to have been effective.We did not find enough evidence to say there was a significantly positiveaverage difference in weekly income. The incentive plan does not appear tohave been effective.O4)O 5) The average difference in weekly income is equal to 0.

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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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C. Predicting Student Success STA believes there is a relationship between high school GPA (on a four-point scale) and college performance (as measured by GPA on a four-point scale). The following data were randomly selected from among students enrolling Fall 2020. HS GPA STA GPA Student 1 HS GPA STAGPA Student 21 2.9 2.5 3.6 3.4 2 3.4 3.1 3.0 22 3.4 4.0 1.7 3 3.1 23 2.9 2.9 1.7 3.0 3.2 3.3 4 24 3.5 5 3.4 25 4.0 3.6 3.6 3.0 26 3.6 3.8 3.2 3.9 3.1 27 8. 4.0 3.9 28 3.4 3.6 3.2 9. 3.0 3.0 29 3.7 10 2.9 2.0 3.0 30 4.0 3.3 4.0 3.2 11 3.3 31 12 3.6 3.8 32 3.7 3.2 3.4 3.0 13 3.7 3.9 33 14 3.8 3.6 34 2.5 2.0 15 2.5 2.5 35 2.9 2.9 3.7 2.2 16 2.9 2.5 36 3.8 17 2.8 2.1 37 2.9 18 3.8 1.7 3.5 38 3.6 3.5 3.6 19 3.7 39 3.6 20 3.9 3.0 40 3.1 3.6 How confident should St. Mary's be regarding the accuracy of their predictions? Why?
C. Predicting Student Success STA believes there is a relationship between high school GPA (on a four-point scale) and college performance (as measured by GPA on a four-point scale). The following data were randomly selected from among students enrolling Fall 2020. HS GPA STA GPA Student 1 HS GPA STAGPA Student 21 2.9 2.5 3.6 3.4 2 3.4 3.1 3.0 22 3.4 4.0 1.7 3 3.1 23 2.9 2.9 1.7 3.0 3.2 3.3 4 24 3.5 5 3.4 25 4.0 3.6 3.6 3.0 26 3.6 3.8 3.2 3.9 3.1 27 8. 4.0 3.9 28 3.4 3.6 3.2 9. 3.0 3.0 29 3.7 10 2.9 2.0 3.0 30 4.0 3.3 4.0 3.2 11 3.3 31 12 3.6 3.8 32 3.7 3.2 3.4 3.0 13 3.7 3.9 33 14 3.8 3.6 34 2.5 2.0 15 2.5 2.5 35 2.9 2.9 3.7 2.2 16 2.9 2.5 36 3.8 17 2.8 2.1 37 2.9 18 3.8 1.7 3.5 38 3.6 3.5 3.6 19 3.7 39 3.6 20 3.9 3.0 40 3.1 3.6 Is high school GPA a good predictor of STA GPA? Why? What STA GPA would you predict for a student with a high school GPA of 3.75? How you would make the prediction.
A health insurance company is looking at the use of its benefits by its members. It randomly selects 500 members for further study, and one of the pieces of information they collect is the amount the amount of money spent on prescription medications over the past year. The average amount among the 500 members is $600 and the SD is $1,000. A histogram of the amounts is quite skewed to the right, and 40 (8%) of the sampled members have spent $5000 or more on prescription medications in the past year. Calculate a 95%-confidence interval for the percentage of all members who have spent $5000 or more on prescription medications in the last year.
Do you think that by choosing the statistical analysis first, and then deciding upon what kind of research plan (i.e., so that the data will suit the analysis) could bias the entire research enterprise?
How do the average weekly incomes of electricians and carpenters compare? A random sample of 17 regions in the United States gave the following information about average weekly income (in dollars). (Reference: U.S. Department of Labor, Bureau of Labor Statistics.) Region 1 2 3 4 5 6 7 8 9 Electricians 464 715 597 464 736 694 744 571 806 Carpenters 542 813 513 476 688 503 789 653 474 Region 10 11 12 13 14 15 16 17 Electricians 592 594 702 579 868 598 597 654 Carpenters 489 647 676 384 817 605 556 505 Does this information indicate a difference (either way) in the average weekly incomes of electricians compared to those of carpenters? Use a 5% level of significance. (a) What is the level of significance? (b) Compute the sample test statistic. (c) Find the P-value of the sample test statistic.
A ski company in Vail owns two ski shops, one on the west side and one on the east side of Vail. Ski hat sales data (in dollars) for a random sample of 5 Saturdays during the ski season showed the following results. Is there a significant difference in sales dollars of hats between the west side and east side stores at the 10 percent level of significance? Saturday Sales Data ($) for Ski Hats Saturday East Side Shop West Side Shop 1 548 523 2 493 721 3 609 695 4 567 510 5 432 532 Click here for the Excel Data File (a) Choose the appropriate hypotheses. Assume μd is the difference in average sales between the east side shop and west side shop. a. H0: μd = 0 versus H1: μd ≠ 0.b. H0: μd ≠ 0 versus H1: μd = 0. multiple choice a b Ski Hat Sales on Five Consecutive Saturdays (n = 5) Saturday East Side West Side 1 548 523 2 493 721 3 609 695 4 567 510 5 432 532
You just finished statistics class and are eager to collect and analyze your own data! You run out and collect data on students' living arrangements (measured as either on-campus housing or off-campus housing) and whether they are involved in extra-curricular activities (measured as either involved or not involved). You want to examine whether there is an equal distribution of students who live on- and off-campus among those are are involved or not involved in extra-curricular activities. You will most likely use ___ to analyze your data. Group of answer choices a z-test a two-sample t-test a one-sample t-test an ANOVA a correlation a chi-square test a z-score a one-predictor regression a two-predictor regression
A ski company in Vail owns two ski shops, one on the west side and one on the east side of Vail. Ski hat sales data (in dollars) for a random sample of 5 Saturdays during the ski season showed the following results. Is there a significant difference in sales dollars of hats between the west side and east side stores at the 10 percent level of significance? Saturday Sales Data ($) for Ski Hats Saturday East Side Shop West Side Shop 1 548 523 2 493 721 3 609 695 4 567 510 5 432 532 Click here for the Excel Data File (b) State the decision rule for 10 percent level of significance. (Round your answers to 3 decimal places.) (c-1) Find the test statistic tcalc. (Round your answer to 2 decimal places. A negative value should be indicated by a minus sign.) (c-2) What is your conclusion? Ski Hat Sales on Five Consecutive Saturdays (n = 5) Saturday East Side West Side 1 548 523 2 493 721 3 609 695…
(6) A student surveys some students on campus in the evening and finds that 16 out of 20 of the students she interviewed are part time students. She uses the data to estimate the percentage of all students who are part time. What type of bias is present in her sample?

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