Question

I need the answer for number 17 to 30. For numbers 17-19, please...

I need the answer for number 17 to 30.

Image transcription text

For numbers 17-19, please refer to the following: The test scores of 19 students are listed below 36 45 49 53 55 56 59 61 62 65 67 72 77 80 81 85 91 94 96 17. Find the 34th percentile. Interpret the result. A. 59; 59% of the scores falls below 34 B. 61; 34% of the scores falls below 61 C. 59; 34% of the scores falls below 59 D. 61; 61% of the scores falls below 34 E 18. Find the 7th decile. Interpret the result. A. 77; 7% of the scores falls below 77 B. 80; 7% of the scores falls below 80 C. 80; 70% of the scores falls below 80 D. 77; 70% of the scores falls below 77 19. Find the interquartile range. A. 24 B. 25 C. 26 D. 27

...

Image transcription text

For numbers 20-25, please refer to the following problem: An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month Production Volume (units) Total Costs ($) January 2018 500 6,000 February 2018 350 4,000 March 2018 450 5,000 April 2018 550 5,400 May 2018 600 5,900 June 2018 400 4,000 July 2018 400 4,200 August 2018 350 3,900 September 2018 400 4,300 October 2018 600 6,000 November 2018 700 6,400 December 2018 750 7,000 20. Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? 1. The monthly total costs will increase by$7.6437 for every one-unit increase in the production volume. Since b &gt; 0, there is a direct relationship between production volume and total costs. III. Because b &gt; 1, there is a very strong positive linear relationship between production volume and total costs. A. i and ii only B. ii only C. ili only D. ii and ii only

...

Image transcription text

21. Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in this problem? 1. Production volume is dependent on total costs. 1I. The predictor and response variables are the production volume and total costs, respectively. III. The total costs can be projected using the simple linear regression equation if the production volume is known. A. i and ii only B. i and ili only C. ii and iii only D. i, ii, and ii 22. Calculate the (Pearson) correlation coefficient between production volume and total costs in this problem. A. 0.8391 B. 0.9571 C. 0.9160 D. 0.9783 23. Which of the following is the most suitable interpretation of the (Pearson) correlation coefficient between production volume and total costs in this problem? A. There is a perfect positive correlation between production volume and total costs. B. There is a very strong positive correlation between production volume and total costs. C. There is a strong positive correlation between production volume and total costs. D. There is a positive correlation between production volume and total costs. 24. The equation of the regression line is given by A. y = -116.01 + 0.12x B. y = 1321.32 - 7.64x C.y = 116.01 + 0.12x D. y = 7.64x + 1321.32 25. How much is the estimated total costs if the corresponding production volume for a particular month is 300 units? A. $274.80 B.$287.13 C. $2,293.11 D.$3,614.43

...

Image transcription text

For numbers 26-27, please refer to the following: The coefficient of variation of the height of 20 people selected at random from a given city is found to be 15%. The weight of the selected group has a mean value 72 kg and a standard deviation 8 kg. 26. The coefficient of variation for the weight of the selected group is A. 1.11% B. 8.33% C. 11.11% D. 83.33% 27. The obtained results show that A. the weight is more variable than height. B. the weight is less variable than height. C. height and weight have the same degree of variation. D. height and weight are independent. 28. The first step in formulating an LP problem is A. graphing the problem. B. identifying the objective and the constraints. C. defining the decision variables. D. understanding the managerial problem being faced. 29. Linear programming theory states that the optimal solution to any problem will lie at A. the origin. B. a corner point of the feasible region. C. the highest point of the feasible region. D. the lowest point in the feasible region. 30. In order for a linear programming problem to have a unique solution, the solution must exist A. at the intersection of the nonnegativity constraints. B. at the intersection of a nonnegativity constraint and a resource constraint. C. at the intersection of the objective function and a constraint. D. at the intersection of two or more constraints.

...

Solved by verified expert

e vel laoreet ac, dictum vit

ec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec aliquet. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. P

Explore over 16 million step-by-step answers from our library

Step-by-step explanation

Do

, ultrices ac magna. Fusce dui lecec facec facor ne

entesque dapibus efficitur laoreet. Nam risus ante, dap

sum dolor sit amet, consectetur adipiscing elit. Nam laciniec facec facce dui lect

risus ante, dapibus

llentesq

s a molestie consequat, ultrices ac magna. Fusc

tri

trices ac magna. Fusce dui lectus, congue ve

Fusce dui lectus, congue vel laoreet ac,

sum dolor sit amet, consectetur adipiscing elit. Nam laciniec facec facce dui lect

risus ante, dapibus

llentesq

m ipsum dolor sit ame

rem ipsum dolor sit amet, consectetur adipiscing elit.

mol

s a molfacilisis. Pellentesque dapibus efficitur laoreet. Nafacilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, daat, ulor nec facilisis. Pellentesque dapibus effi

entesque dapibipisiscing elit. Nam lacinia pulvinar tortor nec facilisat, ulu

a molestie coctum vitae odio. Donec aliquet. Lorem ipsum dolor sit amet

i

usc

cing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec aliquet. Lorem ipsum dolor sit amet, con

usc

ipsum dolor sit amet, consectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec aliquet. Lorem ipsum dolor sit

dictum vitae odio. Done

Student reviews
68% (19 ratings)