You run a regression analysis on two numerical variables x and y, where x is the explanatory variableandY is the response. With the help of statistical software, you obtain the regression equationy = -2.859x + 59.865with a correlation coefficient of r = -0.964. You want to predict what value (on average) for theresponse variable will be obtained from a value of 190 as the explanatory variable.What is the predicted response value?y =(Report answer accurate to one decimal place.)

Regression equation y is. y = -2.859 x + 59.865 Correlation coefficients r = -0.964

Answered: You run a regression analysis on two…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

From a regression equation r2= 0.39 and the slope = -2.8 What is the linear correlation coefficient r?
You run a regression analysis on a bivariate set of data (n = 63). With = 61.1 and y = 27.2, you obtain the regression equation y = 3.192x - 22.251 with a correlation coefficient of r = 0.694. You want to predict what value (on average) for the response variable will be obtained from a value of 10 as the explanatory variable. What is the predicted response value? y = (Report answer accurate to one decimal place.)
Why was the variable “# of customer service representatives” dropped from the model? Write the regression equation. Sales of men’s clothing (predicted) = Are the regression coefficients significantly different from 0? If one mails 10,000 catalogs and has 15 phone lines open, what would the predicted sales of men’s clothing be? How would you interpret the regression coefficient for number of catalogs mailed? What is the final R2 of the model? How would you interpret this? Which of the two independent variables is the most important predictor of the dependent variable? Why?
Suppose that you run a correlation and find the correlation coefficient is -0.281 and the regression equation is y = 27.68 2.2x. The mean for the data values was 4.9, and the mean for the Y data values was 17. AT Test for the slope of the regression line is performed, and the p-value is greater than the level of significance of 0.05. Use the appropriate method to predict the y value when x is 2.3.
The correlation between X and Y is -.27, and the regression equation is Ŷ = - 0.49X + 9.27 before the data are standardised. A: What is the correlation after the data are standardised? B: What would be the standardised regression equation? A: .27, B: ?̂y = .27?x A: -.49, B: ?̂y = - .49?x + 9.27 A: -.27, B: ?̂y = - .27?x A: -.49, B: ?̂y = - .49?x
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 2.5 3 4 5 5.5 Overall Grades 98 95 90 79 75 69 66 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 "Not all points predicted by the linear model fall on the…
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 1.5 2 2.5 3 4 4.5 Overall Grades 97 93 74 73 65 61 60 Table Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal
I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for five 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 2 3 4 5 6 Overall Grades 94 86 79 71 62 Table Step 1 of 6 : Find the estimated slope, y intercept and correlation coefficient Round your answer to three decimal places. Answer
You run a regression analysis on a bivariate set of data (n = 51). You obtain the regression equation y=-4.028r+-18.476 with a correlation coefficient of r=-0.91 (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 170 on the response variable. What is the predicted explanatory value? X = (report 3 decimals)
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.

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS