A regression analysis between sales (in R1000) and price (in rands) resulted in the following equation: -50,000-8x, this equation implies that anOA increase of R1 in price is associated with a decrease of R8000 in salesO B, increase of R1 in price is associated with a decrease of R42,000 in salesO c increase of R1 in price is associated with a decrease of R8 in salesO D. increase of R8 in price is associated with an increase of R8,000 in sales

Given that : In tha given regression equation. Y(cap) = 50,000 - 8x Here, X represents sales { in…

Answered: A regression analysis between sales (in…

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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In a regression model if you drop one insignificant variable then a. R ^ 2 will increase and SSE also will increase . None R ^ 2 will decrease and SSE also will decrease . O d R ^ 2 will increase but SSE will decrease . O e R ^ 2 will decrease but SSE will increase .
4
For the years from 2006 and projected to 2021, the national health care expenditures H, in billions of dollars, can be modeled by H = 2009e0.05194t where t is the number of years past 2005.† In what year are national health care expenditures expected to reach $2.5 trillion (that is, $2500 billion)?
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.904 b=39.953 r2=0.4096 r=-0.64 Use this to predict the number of situps a person who watches 0.5 hours of TV can do (to one decimal place) > Next Question hp Ce
The linear regression equation for predicting systolic blood pressure from age is as follows: y = 42 + 2.5x . Find the residual for a person who is 21 years of age with a systolic blood pressure of 91.9.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.818 b=21.295 r2=0.49 r=-0.7 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
.18x+0.22(600,000-x)=.20(600,000)
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.226 b=33.622 r²-0.4489 r=-0.67 Use this to predict the number of situps a person who watches 3 hours of TV can do (to one decimal place)
In regression equation, slope is the amount increases or decreases in the independent for every 1 unit added in x. O True O False
1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable.
You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are: I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars. Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.131 b=37.124 r2=0.398161 r=-0.631 Use this to predict the number of situps a person who watches 6.5 hours of TV can do (to one decimal place)

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