2. Given the following datalist of the height and weight pairs:Height 68 69 70 70 71 71 72 72 73 73 74 75Weight 151 146 150 160 170 160 163 180 170 175 178 188a. Compute the linear correlation coefficient for the height and weight pairsant interpret it.b. Compute the coefficient of determination and interpret it.c. Find the least squares regression line and interpret the slope.s) d. Test, at the 2% level of significance, whether the variable x is useful forpredicting y based on the information in the height and weight data set.

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Answered: 2. Given the following datalist of the…

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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The following data represent the number of flash drives sold per day at a localcomputer shop and their prices.Price Units Sold34 336 432 635 530 938 240 1a. Develop the estimated regression equation that could be used to predict thequantity sold given the price. Interpret the slope.b. Did the estimated regression equation provide a good fit? Explain.c. Compute the sample correlation coefficient between the price and the number offlash drives sold. Use a= 0.01 to test the relationship between price and units sold.d. How many units can be sold per day if the price of flash drive is set to $28.
Consider the “height-for-age” data below:Table 3: Height for age data Age in Years 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19Heightincm 102 107 112 116 121 126 130 136 143 149 154 158 161 162163a) Make a scatter plot of the data.b) Find the least square regression line and add it to the scatter plot in a). c) Find the coefficient of determination and state what it tells us about the relationship between age and height. d) Going by the relationship between Age and Height that you have established:i) What would the expected value of Height be if Age is 90 years? ii) Will the linear models be the best model for "height-for-age data"? JUSTIFY YOUR ANSWER!
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $140 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 39 22 118 67 77 49 124 66 12 64 128 19 6. 147 9. 118 6. 99 75 127 107 95 99 64 109 209 44 8 293 48 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x. (Round to one decimal place as needed.)
Post secondary education information was examined for a random selection of states. The data below show the number of community colleges in the number of universities for each particular state. Community: 12, 17, 13, 10, 8 University: 4, 6, 5, 4, 3 A. Create a scatterplot of the given data sets B. Find the correlation coefficient of the sets of data. C. Create the equation of the regression line for the data and evaluate it when X=300.
listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $110 million. Use a significance level of α=0.05. Budget ($)in Millions 45 19 112 70 76 53 122 65 7 55 129 21 11 152 10 Gross ($) in Millions 124 8 101 65 123 107 109 103 48 112 204 28 19 282 41 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y=16.516.5+1.31.3x. (Round to one decimal place as needed.) The best predicted gross for a movie with a $110 million budget is ____million. (Round to one decimal place as needed.)
The coefficient of determination (r2) is a measure of the: a.) amount of variance in the dependent variable explained by the independent variable. b.) correlation between two variables. c.) variability of the dependent measure. d.) slope of a regression line.
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)
The paired data below consists of heights and weights of 6 randomly selected adults. Find the linear correlation coefficient, the linear regression line, and predict the weight of a randomly selected person who is 1.69 meters tall. X Height (meters) 1.61 1.72 1.78 1.80 1.67 1.88 Y Weight (kg) 54 62 70 84 61 92
A soda company has a machine that is set to fill each can with 12 ounces of soda. It actually fills each can with between 11.5 and 12.5 ounces. Let X denote the amount of soda put in a randomly selected can. The amount put in each can is uniformly distributed. What is the probability that the put in a randomly selected can less than 11.8 ounces? Find P(X<11.8) A) 0.30 B) 1.23 OC) 0.58 OD) 0.79

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