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 itsbudget is $105 million. Use a significance level of a = 0.05.Budget ($)in MillionsGross ($)in Millions412311475784712064105912722121502 01271811165113112102946498211412228857Click 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.)

Given value X Y X \cdot YX⋅Y X^2X2 Y^2Y2 41 127 5207 1681 16129 23 18 414 529 324…

Answered: Listed below are paired data consisting…

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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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 groes f to budget is $100 million. Use a significance level of a 0.05. Budget (S)in Millions Gross (S) in Millions 45 17 114 67 70 49 117 67 3. 62 128 21 11 152 10 103 72 131 121 105 105 51 95 203 24 13 289 48 114 12 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.)
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
NHL Assists and Total Points A random sample of scoring leaders from the National Hockey League (NHL) showed the following numbers of assists and total points. Based on these data, can it be concluded that there is a significant relationship between the two? Draw the scatter plots for the variables. Assists 59 68 44 65 67 69 Total points 109 101 95 94 91 89
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (lb) Highway (mpg) Which scatterplot below shows the data? A. 40- 20- 2000 5000 2795 3225 3470 32 34 28 Weight (lb) B. 40- 20+ 2000 D 5000 Weight (lb) 4085 4155 2225 25 23 38 C. ● 20+ 2000 ● ● ● ● 5000 Weight (lb) Is there a linear relationship between weight and highway mileage? A. No, there appears to be no relationship. B. Yes, as the weight increases the highway mileage decreases. C. No, there appears to be a relationship, but it is not linear. D. Yes, as the weight increases the highway mileage increases. 40- 20- 2000 3440 29 5000 Weight (lb)
5. The table below shows varying prices of music sold on a streaming service. Determine the linear regression to estimate the weekly sales of albums sold, use your regression to estimate the weekly sales if the price is $9 per album, and state the correlation coefficient, r, and interpret its meaning in the context of this problem. Price ($) Weekly sales (in thousands) $8 440 $8.50 380 $10 $11.50 250 180
Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. y’ = 1.5x - 3 There is no significant correlation between the variables,…
The age and prices of 11 Nissan cars given in the following data: Age (in years) 5 4 6 5 5 5 6 6 2 7 7 Price (in $100s) 85 103 70 82 89 98 66 95 169 70 48 a. Obtain the correlation coefficient between the age and price of the cars. Interpret the value of the correlation coefficient. b. Obtain a regression equation of Price (dependent variable) on Age (Independent variable). c. What will be the Price of the car after 3 years? d. Find the coefficient of determination. Determine the percent of variation that is explained by the regression equation clearly.
JUST ANSWER THE LETTER D AND E A Zumba instructor remembers the data given in the following table, which shows the recommended maximum exercise heart rates for individuals of the given ages. Age (x years) 20 40 60 Maximum heart rate 170 153 136 (y beats per minute) a. Find the linear correlation coefficient for the data. b. What is the significance of the value found in part a? c. Find the equation of the least-squares line. d. Use the equation from part c to predict the maximum exercise heart rate for a person who is 72. e. Is the procedure in part d an example of interpolation or extrapolation?
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.)

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