he table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students, Us nis data, consider the equation of the regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based on the number of ho pent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would no appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 1.5 2.5 3.5 5.5 Overall Grades 96 94 89 87 82 74 68 Tab Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. 田 Tables E Keypac Answer Keyboard Shortc How to enter your answer Submit Answer © 2021 Hawkes Learning o search hp 立

he table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students, Us nis data, consider the equation of the regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based on the number of ho pent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would no appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 1.5 2.5 3.5 5.5 Overall Grades 96 94 89 87 82 74 68 Tab Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. 田 Tables E Keypac Answer Keyboard Shortc How to enter your answer Submit Answer © 2021 Hawkes Learning o search hp 立

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 table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 2 4 5 6 Midterm Grades 67 68 70 79 87 Summation Table x y xy x2 y2 Student 1 1 67 67 1 4489 Student 2 2 68 136 4 4624 Student 3 4 70 280 16 4900 Student 4 5 79 395 25 6241 Student 5 6 87 522 36 7569 Sum 18 371 1400 82 27823 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your…
The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 2323 3434 4040 4646 4747 Number of Bids 11 33 44 55 77 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks. Based on this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict the interception percentage for an NFL quarterback. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. completion percentage 57 58 60 63 64 interception percentage 4.5 4 3 2.5 1 Find the estimated value of y when x=57x=57. Round your answer to three decimal places.
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the equation of the resulting multiple linear regression? starting_salary = 3008.61 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15000.00 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15001.00 + 41.43*GPA + 84.71*years_of_experience + 37.32*civil_service_ratings starting_salary = 2366.77 + 130.25*GPA + 396.39*years_of_experience + 21.67*civil_service_ratings
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.
The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. hours studying 0 1 3 4 5 grades 63 65 80 81 87 Find the value of the coefficient of determination. Round your answer to three decimal places.
The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks. Based on this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict the interception percentage for an NFL quarterback. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. completion 55 59 60 64 66 interception 4.5 3.5 3 2.5 1.5 Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable y^.
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 44 52 54 62 70 Bone Density 346 342 332 325 323 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable yˆ is given by? a. b0 b. b1 c. x d. y Step 4 of 6: Find the estimated value of y when x=52. Round your…
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y^=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Find the estimated value of y when x=52. Round your answer to three decimal places. age 35 41 52 56 66 bone density 358 350 348 332 321
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 00 0.50.5 11 1.51.5 22 3.53.5 44 Overall Grades 8989 8181 7373 7272 6969 6767 6363 Table Copy Data Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1.51.5 2.52.5 33 44 4.54.5 55 66 Overall Grades 9494 9292 8282 7979 7171 7070 6262 Find the value of the coefficient of determination. Round your answer to three decimal places.
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Table Copy Data Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.