You run a regression analysis on a bivariate set of data (n = 10). You obtain the regression equationy = 0.493x + 58.349with a correlation coefficient of r = 0.877 (which is significant at a = 0.01). You want to predict what value(on average) for the explanatory variable will give you a value of 100 on the response variable.What is the predicted explanatory value?X =(Report answer accurate to one decimal place.) Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places)Xy14.8618.4417.3218.818.8821.7622.5423.521021.711 22.0812 26.1613 23.1414 25.4215 28.31626.1817 26.6623456|7∞|9O8567

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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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You run a regression analysis on a bivariate set of data (n=109). With x¯=72.2 and y¯=34.7, you obtain the regression equation y= - 0.898x - 42.514 with a correlation coefficient of r=-0.086. You want to predict what value (on average) for the response variable will be obtained from a value of 140 as the explanatory variable. What is the predicted response value? y =
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, 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 1 1.5 2.5 4 5.5 6 Overall Grades 98 86 85 83 80 78 67 Table Step 1 of 6: Find the estimated slope, y intercept, correlation cofficient Round your answers 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, 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 2 3 4 4.5 5 5.5 Overall Grades 98 95 93 90 89 72 69 Table Copy Data Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
You run a regression analysis on a bivariate set of data (n = 22). With ☎ = 22.3 and y = 58.5, you obtain the regression equation y = 0.842x + 37.664 with a correlation coefficient of r = 0.897. You want to predict what value (on average) for the response variable will be obtained from a value of 180 as the explanatory variable. What is the predicted response value? y = (Report answer accurate to one decimal place.)
You run a regression analysis on a bivariate set of data (n = 120). With i = 66.3 and y = 50.6, you obtain the regression equation y = 4.097x – 11.636 with a correlation coefficient of r = 0.56. You want to predict what value (on average) for the response variable will be obtained from a value of 120 as the explanatory variable. What is the predicted response value? y = (Report answer accurate to one decimal place.)
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=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 0.5 1.5 2 2.5 3 4.5 5 5.5 6 Midterms Grades 60 63 64 69 73 76 82 90 91 95 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: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false Step 4 of 6:…
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?
You run a regression analysis on a bivariate set of data (n = 89). With a = 35.4 and y = 53.5, you obtain the regression equation %3D y = 3.651x – 38.171 0.1. You want to predict what value (on average) for the %3D - with a correlation coefficient of r = response variable will be obtained from a value of 110 as the explanatory variable. What is the predicted response value? y%3D
You run a regression analysis on a bivariate set of data (n = 106). You obtain the regression equation y = 4.241x – 10.085 =0.373 (which is significant at a value (on average) for the explanatory variable will give you a value of 70 on the response variable. with a correlation coefficient of r 0.01). You want to predict what What is the predicted explanatory value? X = (Report answer accurate to one decimal place.)
If the regression equation is ỹ =1.3+0.20x, and r =0.81 then the correlation is equal to O -0.09 O -0.90 O none O 0.20 O -0.20 O 0.90
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, 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 1.5 2 3 4.5 5.5 Overall Grades 100 97 96 85 83 72 67 Table Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places

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