Find the linear equation given the regression results Listed below are PSAT scores and SAT scores from prospective collegeapplicants. The scores were reported by subjects who responded to a request postedby the Web site talk.collegeconfidential.com.207 167 206 197PSAT 183142 193176SAT 2200 2040 1890 2380 2290 2070 2370 1980(1) Is there sufficient evidence to conclude that there is a linear correlation betweenPSAT scores and SAT scores? Use 0.01 as the significance level.(2) One subject not included in the given table had a PSAT score of 229. Find thebest predicted SAT score for this student. Is the result close to the reported value of2400? Sample Size, n:Degrees of Freedom:Correlation Results:Correlation Coeff, r:Critical r:P-Value (two-tailed):Regression Results:Y= b0 + b1x:Y Intercept, b0:Slope, b1:Total Variation:Explained Variation:Unexplained Variation:Standard Error:Coeff of Det, R^2:Adjusted R^2:80061.00000+0.834340.000000.000001.000003380.875003380.875000.000000.000001.000001.00000

Let the regression be used to find the relationship between the independent and dependent variable…

Answered: Listed below are PSAT scores and SAT…

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 volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−50.8+0.3x1+5.1x2, where x1 is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−51.9+0.3x1+4.9x2, where x1 is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables.
A business analyst found a linear relationship between the predicted profit (in thousands of dollars) with the amount of employees hired (think of the units as per person). The resulting regression equation and coefficient of determination were found to be: ŷ = 10 + 4.5x R² = 72% a) Interpret the slope and y-intercept using the guidelines learned in class. b) Find the predicted profit when the you hire 5 employees. c) Suppose that the true profit when 5 employees are hired is $42 thousand dollars. Find the residual. d) What is the correlation coefficient? Round to three decimal places. e) What is the strength of the correlation coefficient?
Suppose the equation of the regression line for the number of emails a person recieves at a particular sales company is given by y=9+19⋅x. Where y is based on the number of accounts the person has, x. If a person has 15 accounts, find the number of emails they will recieve. Number of emails:
Consider the following regression equation: y = -3.9 + 7.2x What does 7.2 depict in the regression equation above? a) The direction of the line. b) The y-intercept. c) The point where x = 0. d) The y when x = 7.2.
An individual wants to determine how much money a boy scout earns from selling popcorn (Y-variable) based on the length of time (in days) that they went out selling (X-variable). Using the following linear regression equation Ŷ = 5 + 20X: a. State the value of the intercept AND the value of the slope (2 points) b. Based on the given regression equation, what can you determine about the direction of the relationship between X and Y (i.e. is it positive or negative)? (2 points) c. If a boy scout sells popcorn for 4 days, how much money is he predicted to earn? (2 points)
nd fill in the coefficients for the regression equation: Y= _+ X1+ X2
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.8 + 0.3x, +4.5x,, where x, is the tree's height (in feet) and x, is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. x, = 70, x, = 8.6 The predicted volume is cubic feet. (Round to one decimal place as needed.)
In 2012, the CDC published data on the average weight of American female children by year. Using ages 1−7 of this data, researchers made a linear regression with age in years as the x variable and weight in pounds as the y variable. The equation of the line of best fit is yˆ=5.78x+17.56. According to the line of best fit, what would you predict the weight would be for a 14-year-old female? Is it reasonable to use this line of best fit to make this prediction?

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