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 equationof the regression line,ŷ = bo + bix, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or maynot 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 correlationcoefficient is not statistically significant.AnswerHow to enter your answer (opens in new window)escStep 3 of 6: 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 thevalue of the independent variable is increased by one unit, then find the change in the dependent variable.LⒸ2022 Hawkes Learning•D>Price in Dollars 22 23 28 41 50Number of Bids 2 3 4 5 9RT6TheThis9< *4)TablesTableCopy DataKeypadKeyboard ShortcutsPrevious step answersSubmit Answer@

Assume that x defines the price and y defines the number of bids.

Answered: The table below gives the list price…

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 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, y = 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 23 26 31 40 48 Number of Bids 3 4 6 7 9 Table Step 5 of 6: Find the error prediction when x = 31. Round your answer to three decimal places.
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 = bo + bịx, 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 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
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+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 106 108 117 181 193 Number of Bids 10 15 16 17 18 Table Find the estimated y-intercept and correlation coefficient ..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, ŷ = bo + bịx, 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 0.5 1.5 2.5 3 4 4.5 Overall Grades 89 86 81 79 72 67 62 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.
The equation of a regression line, unlike the correlation, depends on the units we use to measure the explanatory and response variables. Here is the data on percent body fat and preferred amount of salt. Preferred amountof salt x 0.2 0.3 0.4 0.5 0.6 0.8 1.1 Percent body fat y 21 30 23 30 39 24 31 In calculating the preferred amount of salt, the weight of the salt was in milligrams. (a) Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in milligrams. (Round your answers to one decimal place.) ŷ = + x (b) A mad scientist decides to measure weight in tenths of milligrams. The same data in these units are as follows. Preferred amountof salt x 2 3 4 5 6 8 11 Percent body fat y 21 30 23 30 39 24 31 Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in tenths of milligrams. (Round your intercept to one decimal place and your slope to two…
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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 = bo + bịx, 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 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 5 of 6: Determine the value of the dependent variable y at x = 0. Answer 囲 Tables 国 Keypad Keyboard Shortcuts Previous step answers O bo O b, Ox Oy
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, y = bo + 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 58 60 61 62 65 Interception Percentage 5 4.5 4 3.5 3 Table Copy Data Step 5 of 6: 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 ŷ. Tables Keypad Keyboard Shortcuts Next
The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x , for using the number of absences to predict a student's overall grade in the class. 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. Number of Absences Grade1 3.72 3.33 3.14 2.96 2.47 2.28 1.9 Find the value of the coefficient of determination. 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, y = bo + 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 2 3 Midterm Grades 71 72 Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Answer How to enter your answer (opens in new window) 4 5 6 73 77 86 Tables Table Copy Data Keypad Keyboard Shortcuts
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, 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 35 43 53 54 55 Bone Density 350 340 339 321 310 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer
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 = bo + bjx, 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 35 50 54 61 66 Bone Density 354 353 350 334 332 Tab Copy Data Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. 田 Tables 國 Key Answer Keyboard Sho How to enter your answer (opens in new window) Previous step ar Submit An © 2022 Hawkes Learning tv APR 24 MacBook Pro

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