9:13 a O 1 •V a l 44%.A ilearning.com+10retry this question belowYou run a regression analysis ona bivariate set of data (n = 34).With a = 64.7 and jobtain the regression equationy = – 0.544x + 27.47466.8, youwith a correlation coefficient ofr = - 0.128. You want to predict whatvalue (on average) for the responsevariable will be obtained from a value of140 as the explanatory variable.What is the predicted response value?y =(Report answer accurate to one decimalplace.)Question Help: DPost to forumSubmit Question

The Regression equation we obtained and given is, y=-0.544x+27.474

Answered: You run a regression analysis on a…

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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It is known that the linear regression equation: y= -2.88+1.77x, with a coefficient of determination of 0.81. Based on the two information, the correlation coefficient is
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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 and obtain the regression equation y 3.176x +124.355 with a correlation coefficient of r = - 0.748. You want to predict what value (on average) for the response variable will be obtained from a value of x = 150 as the explanatory variable. What is the predicted response value? y = (Report answer accurate to one decimal place.)
A researcher studied the relationship between the amount of carbohydrates (x) and the amount of salt (y) in different food products. sample of 36 food products yielded these calculations: r = -0.1245, ŷ=0.5545– 0.1636x According to the correlation, if a food contains more carbohydrates, is it likely to contain more salt or less salt? Why or why not?
A linear relationship exists between two variables x and y. The correlation coefficient was calculated for the sample data and is equal to -0.93. Using the estimated regression equation, a straight line that will best fit the data points can be drawn through the points on the scattergram. The line slopes downward from left to right and the points are not scattered close to the line. True or false
A sample of 60 women is obtained, and their heights (in inches) and pulse rates (in beats per minute) are measured. The linear correlation coefficient is 0.263 and the equation of the regression line is y=17.9+0.940x, where x represents height. The mean of the 60 heights is 63.3 in and the mean of the 60 pulse rates is 76.8 beats per minute. Find the best predicted pulse rate of a woman who is 67 in tall. Use a significance level of α=0.05.LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r.Question content area bottomPart 1The best predicted pulse rate of a woman who is 67 in tall is enter your response here beats per minute. (Type an integer or decimal rounded to two decimal places as needed.)

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