### Multiple Regression Model AnalysisA multiple regression model was developed to predict the domestic gross for movies based on the production budget, opening weekend gross, and number of stars.**Statistical Analysis:**The overall F-test p-value equals 0.252. Given this information, consider the significance level (alpha) of 0.05.**Question:**What conclusion can you make at alpha = 0.05?**Options:**1. All of the variables contribute to the model.2. At least one of the variables contributes to the model.3. None of the variables contribute to the model.**Explanation:**Since the p-value (0.252) is greater than the alpha level of 0.05, we fail to reject the null hypothesis. This suggests that there is insufficient evidence to conclude that any of the variables significantly contribute to the model in predicting domestic gross.

A regression model is used to predict the domestic gross for movies based on the production budget,…

Answered: A multiple regression model was fit to…

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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Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min Temperature (°F) 786 1091 1135 828 849 1092 64.5 85 82.4 68.5 75.2 87.5 What is the regression equation? y = + X (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)
1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable.
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) PICK THE CORRECT ANSWER [A] We can be 98% confident that when the average weekly wages of state government employees is $878, the average weekly wages of…
Save The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 776 1173 1034 951 975 1214 D Temperature (°F) 70.1 89 77.4 76.2 77 92.6 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) Incorrec ary ns
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A regression was run to determine if there is a relationship between hours of study per week (z) and the final exam scores (y). The results of the regression were: y=ax+b a=6.578 b-20.35 r-0.3721 r=0.61 Use this to predict the final exam score of a student who studies 7 hours per week, and please round your answer to a whole number.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05 Right Arm 101 100 94 75 Left Arm 174 167 146 144 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is (Round to one decimal place as needed.) 76 144 CRITS
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right am blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 100 mm Hg Use a significance level of 0.05. Right Arm 103 102 95 78 Left Arm 175 169 147 146 144 m Click the icon to view the critical values of the Pearson correlation coetticient r The regression oquation is y =+O (Round to one decimal place as needed) Given that the systolic blood pressure in the right arm is 100 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg (Round to one decimal place as needed.)
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The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 784 838 822 949 1188 813 Temperature (°F) 65.7 67.8 66.2 79.9 92.3 73.5 What is the regression equation? What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000chirps per minute are? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…

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