You are investigating the link between the number of customers visiting a website (X) and the number ofproducts sold (Y). You get the following results in Excel:Sales vs Visitors100959085807570y = 0.0088x + 18.48R2 = 0.70266560555050005500600065007000750080008500Visitors(a) What is the slope of the regression line?(see information in the picture -equation located below the regression line)(b) Write the regression equation, y =(see information in the picture -equation located below the regression line)(c) If the website has 6,000 visitors this month, how many sales per month would you expect?Sales

Answered: Image /qna-images/answer/b63ebd48-4bb8-4378-b8b6-5625fad375a9.jpg

Answered: bu are investigating the link 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 regression was run to determine if there is a relationship between hours of study per week (z) and the final exam scores (y). The results of the regression were: y=ax+b a=6.578 b-20.35 r-0.3721 r=0.61 Use this to predict the final exam score of a student who studies 7 hours per week, and please round your answer to a whole number.
please only answer the last part "Suppose that real income per capita in New Jersey increases by 1% in the next year. Use the results in column (4) to predict the change in the number of traffic fatalities in the next year. "
A regression analysis was performed to determine if there is a relationship between hours ofTV watched per day r) and number of sit ups a person can do (y). The results of the regression were: у-ах+b a=-0.827 b=35.329 r2=0.540225 r=-0.735 Use this to predict the number of sit ups a person who watches 13.5 hours of TV can do, and please round your answer to a whole number.
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.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Explain how to find se
A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 10 8 6 13 19 18 27 10 7 Money 58 25 41 51 84 81 87 45 15 1. The equation of the linear regression line is: ˆyy^ = ______ +_____ xx (Please show your answers to two decimal places)
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x= 10 wins (c) x=21 wins (d) x= 15 wins The equation of the regression line is y = x+ | (Round to two decimal places as needed.) !!
Is it reasonable to interpret the y-intercept of the regression line? Why or why not? One home that is 1,750 square feet is listed at $590,000. Is this home's price above or below average for a home of this size? Use residuals and show your work to answer. footaget) ## (Intercept) 21.14411 136.31449 0.155 0.87954 ## footage 0.28388 0.08516 3.333 0.00667 ** ## Residual standard error: 71.64 on 11 degrees of freedom ## Multiple R-squared: 0.5025, Adjusted R-squared: 0.4573 ## F-statistic: 11.11 on 1 and 11 DF, p-value: 0.006671
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? E Click the icon to view the table of regression equations. Choose the correct answer below. O A. The equation CITY = 6.65 - 0.00161WT + 0.675HWY is best because it has a low P-value and the highest adjusted value of R2. O B. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it has a low P-value and the highest value of R?. OC. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it uses all of the available predictor variables. O D. The equation CITY = - 3.14 + 0.823HWY is best because it has a low P-value and its R2 and adjusted R? values are comparable to…
Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight ), and height of the father ( fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 522.303829 2 104.004228 8.49446952 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 Calculate the test statistic that is labeled "C" in the output. t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, Prob > F 37) = R-squared Adj R-squared = Root MSE 40 12.24 0.0001 = 0.3983 0.3657 2.9145 .3591375 -.0797093 -15.32021 = [95% Conf. Intervall .9567683 .4804261…
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day () and number of sit ups a person can do (y). The results of the regression were: y=ax+b a=-1.153 b=22.899 r2=0.649636 r=-0.806 Use this to predict the number of sit ups a person who watches 8 hours of TV can do, and please round your answer to a whole number.

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