7Given are five observations for two variables, and y.The estimated regression equation for these data is ŷ = 74.06 - 2.79x.a. Compute SSE, SST, and SSR.SSE(to 2 decimals)SST(to 2 decimals)SSR(to 2 decimals)b. Compute the coefficient of determination 7². Comment on the goodness of fit.*(to 3 decimals)The least squares line provided an goodfit;c. Compute the sample correlation coefficient. Enter negative value as negative number.(to 3 decimals)Hide FeedbackPartially CorrectDOD000F5F4@O:F2C#80F3$Question 2Hint(s) Check My W49 15 17 2056 57 40 21 15% of the variability in y has been explained by the estimated regression equation (to 1 decimal).AAADII۴۹۹F7%[XiYi6F6&7*FB9F9-0F10-1

For the given data Find all the requires blanks

Answered: Xi Yi Hint(s) Check M 9 15 17 20 57 40…

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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Bloomberg Intelligence listed 50 companies to watch in 2018 (www.bloomberg.com/features/companies-to-watch-2018). Twelve of the companies are listed here with their total assets and 12-month sales. Total Assests ($ billions) 134.47 12-Month Sales ($ billions) Total Assests ($ billions) 12-Month Sales Company Eni SpA Discovery Communications Dong Energy Company AMC Entertainment ($ billions) 68.13 6.59 9.81 4.19 16.15 DSV 6.14 10.54 20.5 Alaska Air Boohoo.com 9.16 10.7 6.9 AMD 3.37 4.62 0.235 0.545 25.11 Cabot Oil & Gas 5.22 1.58 Danone 52.12 Engie 166.84 72 Experian 7.69 4.34 E Click here for the Excel Data File a. Draw a scatter diagram. 1. On the graph below, use the point tool to plot the point corresponding to the first Sales and her Earnings Sales1). 2. Repeat the process for the remainder of the sample (Sales 2, Sales 3, ... ). 3. To enter exact coordinates, dooble-click on the point and enter the exact coordinates of x and y. Tools 90 80 point 2 point 3 70 Ch13_40 18e.xlsx…
1.
Calculate two lines of regression and calculate a linear regression equation to model the data given below: years (1980,1985,1990,1995,2000) Enrolment ( 21,25,29,39,47)
6, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
Find the regression equation Student 1 4 5 6 7 8 9 10 Placement Exam 83 89 92 77 81 81 85 85 87 84 GWA 83 85 90 80 83 85 87 84 90 85 Select the correct response: y=35.39-0.5901x y=35.39x+0.5901 y=0.5901x-35.39 y=35.39+0.5901x 3. 2.
You believe that the price of Zoom Videoconferencing stock and the price of American Airlines stock will move in opposite directions. In order to test this relationship, we do a simple regression with the following variables:A - dependent variable : month end price of American Airlines stockZ - independent variable: month end price of Zoom Videoconferencing stock Data from April 2019 through December 2020 (21 observations) is availableBased on the data, we compute the following:Var (Z) = 20927.702Cov (A,Z) = -899.153E(A) = 20.790E(Z) = 187.530Std Error of Estimate = 6.088TSS = 1476.830 Consider the equation At = b0 + b1 Zt + εtBased on the numbers given above, complete the following table Variable Estimate Std error t-statistic Slope b1 .00941 Constant b0 2.2088 R-square N/A N/A F statistic N/A N/A Are the coefficients (slope and/or constant) significant at the .05 level?
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
5. For the following set of data: Y 1 10 5 4 4 13 a. Find the regression equation for predicting Y from X. b. Does the regression equation account for a significant portion of the variance in the Y scores? Use a = .05 to evaluate the F-ratio %3D X27 33
The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:
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B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…
4)

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