**Regression Analysis and House Pricing**Regression analysis was applied between House Price (in $1000s) and square footage of the house, and the following regression function was obtained:\[ \hat{y} = 100 + 5x \]The above equation implies that an increase of _____.- ○ 1 in square footage is associated with an increase of $5,000 in price- ○ 5 in square footage is associated with an increase of $1,000 in price- ○ $1 in square footage is associated with an increase of $5,000 in price- ○ 1 in square footage is associated with an increase of $56,000 in priceThis equation demonstrates how variations in the square footage (x) affect the predicted house price ($\hat{y}$). The coefficient of $x$, which is 5, indicates the change in price per unit increase in square footage.

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Answered: Regression analysis was applied between…

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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A researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content. His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is ŷ= -299.48 + 4.35 x Calories 186 181 176 149 184 190 158 139 175 148 Sodium 495 477 425 322 482 587 370 322 479 375 Interpret the slope in terms of this problem. If appropriate, find the sodium content if the calorie content is 170. If not, why? If appropriate, find the sodium content if the calorie content is 136. If not, why?
2. The table below lists the annual land-line phone cost per costumer: Year 2012 2013 2014 2015 Cost ($) a. 692 610 Find a linear regression model for this data b. Interpret the slope of the model 580 C. Predict the annual land-line phone cost per customer in 2022 495 2016 434
A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
Show your work please.
While collecting data on shoe sizes (y) compared to heights in inches (x) of male students in the class a student found that the shoe sizes ranged from size 7 to size 11 and the heights of the students ranged from 60 to 72 inches. The student ran a linear regression to get the function = 1 -x- 3 13 where y is the shoe size and is the height of the person in inches. What would be the shoe size for a student who was 73 inches tall? Shoe sizes only show up in incriments of 0.5 (ie. 7, 7.5, 8, 8.5, 9, 9.5, ....) so round to the nearest 1/2 shoe size. Show all your work.
A researcher that there is a linear association between the level of potassium content (y) in milligrams and the amount of fiber (x) in grams in cereal. The regression line for the data is computed to y=37+28x rate. It was also computed that r=.59 A. What does the value . 59 tell you? B. What does the value 37 tell you? C. What does the value 28 tell you ? 2. For the line in question 1 what percentage of variability in potassium can be explained by variability in fiber?
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed. wage = -3.07 + 1.52 educ Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1
A regression analysis between sales ( Y in $1,000 ) and advertising (X in $1,000) resulted in the following equation = 14,200 + 2.6 X The above equation implies that … … an increase of $ 14,200 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 2,600 in advertising is associated with an increase of $ 1,000 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 2,600 in sales
A grocery store is interested in how customers' income affects the amount of money they spend each week. A regression analysis is performed to test this analysis. The results of the analysis are that the intercept is $17.80 and the slope is 0.0012. Based on these results, what is the predicted weekly grocery expenditure (to the nearest cent) for a household with an income of $65,000? $95.80 O$78.00 $45.23 $17.80 Ho: mean weekly expenditure = $78.00

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