6. Each year, a baseball team sells boxes of chocolates as a fundraiser to lower the cost of team fees.The price of the chocolates and the number of boxes sold varies each year. The information fromfive years of sales is given in the table below.Price perbox (S)3.004.005.506.508.00Воxes53033360177713161019solda. Find the regression equation in the form y = ax' + bx² +cx +d that best approximates thedata. Express the values of a, b, c, and d to the nearest hundredth. ib. Use the equation to find the number of boxes, to the nearest whole number, that the team willsell if they charge $4.35 per box.c. One year, the team only sold 125 boxes of chocolates. What price did they charge for eachbox?d. If the team raises the price too high, they will not sell any boxes. Use your regressionequation to predict the price of a box that will result in zero boxes sold.

Answered: Image /qna-images/answer/06b35940-3552-4f81-9657-a7d867c82edf.jpg

Answered: 6. Each year, a baseball team sells…

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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Use the given data to find the scatter plot, equation of the regression line, and prediction. 4) Managers rate employees according to job performance and attitude. The results for several randomly selected employees are given below. Performance 59 63 65 69 58 77 76 | 69 70 64 Attitude 72 67 78 82 75 87 92 83 87 78 What function do you use to see the scatterplot on the calculator. Scatterplot from the calculator:
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is _______ fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since the sample size is small, the prediction is not appropriate. B. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. C. Since all of the requirements…
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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 130 380 80 270 (a) x= 150 calories (c) x-120 calories 190 160 415 180 465 130 350 (b) X3D90 calories (d) x= 60 calories 540 (a) Predict the value of y for x= 150. Choose the correct answer below. O A. 212.451 B. 347.151 C. 414.501 O D. not meaningful (b) Predict the value of y for x= 90. Choose the correct answer below. O A. 212.451 O B. 347.151 es OC. 279.801
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Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 658.
4)
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y (b) x = 649 feet (d) x = 724 feet 766 620 520 508 494 484 (a) x = 503 feet 51 46 44 43 39 38 (c) x = 318 feet Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. O B. O C. O D. 60- 60- 60 60- 0- 800 800 800 Height (feet 800 Height (feet) Height (Teet) Stories Stories:
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