One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region.Complete parts (a) through (h) below.Click the icon to view the housing data.(d) Is there a linear relation between square footage and asking price?O NoYes(e) Find the least-squares regression line treating square footage as the explanatory variable.y = 0.16 x++(15.65)(Round to two decimal places as needed.)(f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.OA. For every additional square foot, the selling price increases bythousand dollars, on average.(Round to two decimal places as needed.)OB. For every additional thousand dollars in selling price, the square footage increases by(Round to two decimal places as needed.)OC. For a house that is sold for $0, the predicted square footage is(Round to two decimal places as needed.)OD. For a house that is 0 square feet, the predicted selling price is thousand dollars.(Round to two decimal places as needed.)OE. It is not appropriate to interpret the slope.square feet, on average. 12:38Data TableSquare Footage, x214832311177198830642735414622152625162917733887KOne of the biggest factors in determining the value of a home is the square footage. The accompanying datarepresent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in acertain region. Complete parts (a) through (h) below.Click the icon to view the housing data.|||=PrintSelling Price ($000s), y371.1382.2197.6339.9614.9364.7632.7377.7427.5285.9268.9701.4DoneOVo) 10ا... 46 ... 248%X

Given is the data on the selling price and area (square feet) of houses. We need to predict the…

Answered: (d) Is there a linear relation 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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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
In regression analysis, the coefficient of determination R2 measures the amount of variation in y that is:
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept −12.201 6.560 −1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 What is the regression equation? Multiple Choice Ŷ = 2.195 − 12.201X Ŷ = −12.201 + 2.195X Ŷ = 12.201 + 2.195X Ŷ = 2.195 + 12.201X
What is the dollar amount of change in sales for each new year according to the regression (slope) model? Do not use commas or $ in your answer.
Match the coefficient of determination to the scatter diagram. The scales on the x-axis and y-axis are the same for each scatter diagram. (a) R2=0.12, (b) R2=0.90, (a) Scatter diagram . (b) Scatter diagram . (c) Scatter diagram
Match the coefficient of determination to the scatter diagram. The scales on the x-axis and y-axis are the same for each scatter diagram (a) R2 0.90, (b) R2 0.58, (c) R2 =1 (a) Scatter diagram Explanatory (b) Scatter diagram (c) Scatter diagram Explanatory III Explanatory
Use the cost model screenshot attached to answer the question. Thanks for the help. Use the weekly cost model to estimate the total weekly cost when the weekly demand is 147. Round to the nearest dollar. $
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.
How much should a healthy Shetland pony weigh? Let x be the age of the pony (in months), and let y be the average weight of the pony (in kilograms). x 3 6 12 20 26 y 60 95 140 160 189 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. Flash Player version 10 or higher is required for this question. You can get Flash Player free from Adobe's website. (b) Would you say the correlation is low, moderate, or strong? low moderate strong Would you say the correlation is positive or negative? positive negative (c) Use a calculator to verify that x = 67, x2 = 1265, y = 644, y2 = 93,546, and xy = 10,544. Compute r. (Round your answer to three decimal places.) As x increases from 3 to 26 months, does the value of r imply that y should tend to increase or decrease? Explain your answer. Given our value of r, y should…
B-4 A toy store manager would like to know how the price can affect the sales of toys. In his data, he obtained 100 pairs of prices (unit: £) and volume of sales (unit: hundreds) for the toys. A simple linear regression was run with Sales as the dependent variable and Price as the independent variable with the following results. Regression Statistics R Square Adj. RSqr StErr of EST 0.876 0.767 0.701 4.184 Summary Table Variable Coeff. Std. Err Intercept 64.742 11.310 Price -2.645 0.602 (a) Write down the estimated regression equation. Explain this regression equation. (b) What's the value for R Square? Explain the meaning of this value. (c) Test the significance of the model at a=0.05 level. Write down the hypothesis you are testing, the statistic you use to evaluate the test, and your conclusion. (d) Use the regression output to construct a 99% confidence interval for the predicted sales when the price is set to be 15. (e) A colleague in the toy store claims that £1 increase in the…
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
In bivariate regression, the value of Y when X equals 0 is: Group of answer choices Intercept (b0) Residual Slope (b1)

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