A regression analysis between sales (in $1000) and price (in dollars) gives the following equation:ý = 40, 000 – 5xWhich of the following is a correct interpretation?O a. An increase of $1 in price is associated with a decrease of $5 in salesO b. An increase of $1 in price is associated with a decrease of $35, 000 in salesO C. An increase of $5 in price is associated with a increase of $5, 000 in salesO d. An increase of $1 in price is associated with a decrease of $5, 000 in sales If r = 0.6, the percentage of variation in y explained by x is 60%.Select one:O TrueO False

We have given that The regression equation is, y^ = 40000 - 5x and r = 0.6

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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Using the regression formula with a slope = 5000 and intercept = 10,000, what would the predicted income be for someone who has 15 years of education? A. 60,000 B. 150,000 C. 85,000 D. 75,000
Suppose trips/wk=3.1 –0.15(dist) is a linear model that predicts the number of supermarket trips a family makes per week when they live a certain distance (in miles) from a supermarket. It was established by sampling people who live within 10 miles of a supermarket. Which of the following is the correct interpretation of the slope? a. For each additional trip that the family makes, they live 0.15 miles away from the store b. For each additional mile away from the store the family lives, they make 0.15 more visits per week c. For each additional mile away from the store the family lives, they make 0.15 fewer visits per week d. For each additional trip they make to the store, they live an additional 3.1 miles away. e. For each additional mile away they live, they make 3.1 more trips to the stor.
Medical records indicate that people with more education tend to live longer; the correlation is 0.91. The slope of the linear model that predicts lifespan from years of education suggests that on average people, tend to live 1.46 extra years for each additional year of education they have. The slope of the line that would predict lifespan from years of education is: 1.46 91 146 0.91
The accompanying data represent the yearly amount of solar power installed (in megawatts) in a particular area from 2000 through 2008. The trend forecasting equations below were found, where X is the number of years after 2000. Complete parts (a) through (d) below. = -10.711 +28.9000X₁ ₁ = 22.70 +0.259X; +3.5801X? Click the icon to view the data table. a. Compute the standard error of the estimate (Syx) for each model. Linear Quadratic Syx 22.431 8.032 (Round to three decimal places as needed.) b. Compute the MAD for each model. Linear Quadratic MAD 64.222 66.873 (Round to three decimal places as needed.) c. On the basis of (a) and (b) and the principle of parsimony, which forecasting model would you select? The model with the smallest values of Syx and MAD should be used, which is the quadratic model.
Suppose trips/wk =3.1 -0.15(dist) is a linear model that predicts the number of supermarket trips a family makes per week when they live a certain distance (in miles) from a supermarket. It was established by sampling people who live within 10 miles of a supermarket. Which of the following is the correct interpretation of the slope? O a. For each additional trip that the family makes, they live 0.15 miles away from the store O b. For each additional mile away from the store the family lives, they make 0.15 more visits per week O. For each additional mile away from the store the family lives, they make 0.15 fewer visits per week O d. For each additional trip they make to the store, they live an additional 3.1 miles away. O e. For each additional mile away they live, they make 3.1 more trips to the stor.
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?
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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Suppose that the number of tee shirts sold (N) depends linearly on the price charged (x). Write an equation showing this dependence.

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