16. Rescale the following output that has been run through Regression Data Analysis?InterceptX1 - $1004.323.7X2 - $200X3 - 10mpg -98X4 - 20mpg .21X5 – Silver 3.21.2X6 – Black2.1X7 - $300X8 – 30mpg 0X9 – Red

Given information: The output of regression model is given.

Answered: Rescale the following output that has…

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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Refer to the Baseball 2018 data, which reports information on the 2018 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions. Click here for the Excel Data Filea-1. Draw a scatter diagram.1. On the graph below, use the point tool to plot the point corresponding to the Attendance and its team salary (Salary 1).2. Repeat the process for the remainder of the sample Salary 2, Salary 3, … ).3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y. a-2. From the diagram, does there seem to be a direct relationship between the two variables?multiple choice 1 Yes No b. What is the expected attendance for a team with a salary of $100.0 million? (Round your answer to 4 decimal places.) c. If the owners pay an additional $30 million, how many more people could they expect to attend? (Round your answer to 3…
Q5/ Use Linear Regression to fit the following data: 1 2 4 5 6. Y 4 9 10 10 8
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)
A high R2 is all that is needed to determine if a regression is a good model of a causal process. A. True B. False
Calculate the regression coefficient and obtain the lines of regression for the following data: USE MICROSOFT EXCEL
Briefly describe what is meant by the problem of errors in measurement of the predictor variables and describe its effect on a regression analysis.
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
Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.
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
Using the data in the Excel spreadsheet "auto.xlsx", estimate a regression to answer the following question. A 1 inch increase in LENGTH corresponds to a _________________ increase in MPG (miles per gallon). Use negative values if it results in a decreased price. Round your answers to two decimals. make price mpg rep78 headroom trunk weight length turn displacement gear_ratio foreign AMC Concord 4,099 22 3 3 11 2,930 186 40 121 3.58 Domestic AMC Pacer 4,749 17 3 3 11 3,350 173 40 258 2.53 Domestic AMC Spirit 3,799 22 3 12 2,640 168 35 121 3.08 Domestic Buick Century 4,816 20 3 5 16 3,250 196 40 196 2.93 Domestic Buick Electra 7,827 15 4 4 20 4,080 222 43 350 2.41 Domestic Buick LeSabre 5,788 18 3 4 21 3,670 218 43 231 2.73 Domestic Buick Opel 4,453 26 3 10 2,230 170 34 304 2.87 Domestic Buick Regal 5,189 20 3 2 16 3,280 200 42 196 2.93 Domestic Buick Riviera 10,372 16 3 4 17 3,880 207 43 231 2.93 Domestic Buick Skylark 4,082 19 3 4 13 3,400 200 42 231…

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