Square Footage, x219231781077202631052860394421502507170716993718Selling Price ($000s), y378.1373.7181.9346621.5383.6601.1367.4409.1298.1257.3675.2 KOne 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.(a) Which variable is the explanatory variable?Square FootageSelling Price(b) Draw a scatter diagram of the data. Choose the correct scatter diagram below.O A.4000-1000+150r=●●700B.YesNoАу700-150-1000:………4000C.700-150+1000…...(c) Determine the linear correlation coefficient between square footage and asking price.(Round to three decimal places as needed.)(d) Is there a linear relation between square footage and asking price?4000QO D.4000Ay1000-1000(e) Find the least-squares regression line treating square footage as the explanatory variable.y=x+(Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.)4000Q

Answered: Image /qna-images/answer/b0cc931b-1d61-4f89-af0c-bce50858a7c0.jpg

Answered: (a) Which variable is the explanatory…

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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2
Match the linear correlation coefficient to the scatter diagram. The scales on the x- and y-axes are the same for each diagram. (a) r = -1 (b) r= -0.933 (c) r=-0.523 (d) r= -0.038 Click the icon to view the scatter diagrams. r= -0.933 r= -1 r= -0.523 r=-0.038 Drag each of the r-values given above into the appropriate area below. Q Response Explanatory Response Explanatory Q *** Response Explanatory Q Response Explanatory
Determine whether the data represents a correlation with causation or a correlation without causation. Explain.
Determine the type of direction of correlation that you would expect of the given case / situation. Speed of wind turbines and amount of electricity generated. no correlation positive correlation zero correlation negative correlation
Please ensure the work is legible. Thanks
Match the linear correlation coefficient to the scatter diagram. The scales on the x- and y-axes are the same for each diagram. (a) r= - (b) r= - 0.546 0.025 0.946 (c) r= - (d) r= - 1 Click the icon to view the scatter diagrams. ..... r= - 0.025 r= - 0.546 r= - 0.946 r= - 1 Drag each of the r-values given above into the appropriate area below. Explanatory Explanatory Explanatory Explanatory Response Response Response Response • .
PLEASE SHOW AN EXPLANATION FOR EACH PART
Which correlation coefficient indicates that you have the strongest connection between the variables in the data? O r= 0.88 O r= -0.89 O r= 0.93 O r= -0.95 ent.mastensonnect.com/ Ipe bese to search
please solve A, B, and D ch 12
A scatterplot of two variables is a picture of the relationship represented in a correlation. Group of answer choices True False
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (lb) Highway (mpg) Which scatterplot below shows the data? A. 40- 20- 2000 5000 2795 3225 3470 32 34 28 Weight (lb) B. 40- 20+ 2000 D 5000 Weight (lb) 4085 4155 2225 25 23 38 C. ● 20+ 2000 ● ● ● ● 5000 Weight (lb) Is there a linear relationship between weight and highway mileage? A. No, there appears to be no relationship. B. Yes, as the weight increases the highway mileage decreases. C. No, there appears to be a relationship, but it is not linear. D. Yes, as the weight increases the highway mileage increases. 40- 20- 2000 3440 29 5000 Weight (lb)
Would it be OK to use the line to predict the age of the wife if the husband is 80 years old? Explain your answer.

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