A regression model may be made more accurate by:Select one:O a. increasing the number of observationsO b. using the high-low (2 factor) algorithmO c. re-ordering the data from the lowest Y-value to the highest Y-valueO d. setting the intercept as the data's point of originIn long term management decision-making the relevant profit measure is:Select one:O a. The Gross Profit MarginO b. The Opportunity CostO c. The Contribution MarginO d. The Segment Margin

It is given that the statement about to the regression model. Here, need to find out the correct…

Answered: A regression model may be made more…

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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The point (9.1,71) is a point on the scatterplot. Draw the graph of the regression line on the scatterplot on the back of this paper using the y-intercept and the point(I = 3,y = 191). Indicate the residual for z = 9.1 by drawing the vertical line between(9.1, 71) and the corresponding point on the regression line. Will the residual be a positive or negative value?(f) Find the value of the residual for x = 9.1.
The scatterplot below shows Olympic gold medal performances in the long jump from 1900 to 1988. The long jump is measured in meters. Use the regression line to predict the average predicted long jump distance in 1950. A. The average predicted long jump distance in 1950 is 7.94 meters. B. The average predicted long jump distance in 1950 is 362.7 meters. C. The average predicted long jump distance in 1950 is 3,054 meters. D. The average predicted long jump distance in 1950 is 6.893 meters.
Report the equation of the regression line and interpret it in the context of the problem
a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
2. A sample of small cars was selected to attempt to use the horsepower (x) in hp of the car to predict the fuel efficiency (y) in miles per gallon. A researcher fitted a linear regression model. ŷ-44.0 -0.150x a) Interpret the slope of the regression line. b) Find the predicted fuel efficiency for a horsepower of 150 hp? c) If the fuel efficiency for a car of horsepower of 150hp had an actual fuel efficiency of 25mpg, what is the residual (error) for this car? d) Calculate the correlation coefficient. e) What is the strength of the correlation coefficient? R²=68% f) Interpret the y-intercept.
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 99% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $925. The equation of the regression line is
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
An ice cream truck owner collects data on the number of sales made each day and the average temperature that day. He computes a regression line for predicting the number of sales based on how far the daily temperature is from freezing (0 degrees Celsius) and finds sales = 3.22 - 1.8 (degrees over 0 Celsius). Identify the "y-intercept". A. -1.8 B. 1.8 C. 3.22 D. 0
Please answer letters b-e.
In simple linear regression, the coefficient of determination measures: a.The amount of variability of the y variable that is explained by the x variable b.The amount of variability of the x variable that is explained by the y variable c.The amount of variability between the treatments d.The amount of variability within the treatments
In linear regression analysis, the coefficient for the x-variable when the y-variable is regressed on the x-variable can be thought of as: Note: more than one answer may be correct Group of answer choices How much the value of the predicted y-variable will change when the x-variable changes by one unit. In the simple (two variable) linear regression model, the coefficient can be thought as the slope coefficient that measures the responsiveness of y to changes in x. The estimated coefficient will change if the sample containing x and y changes. The sample coefficient is an estimate of the population coefficient Before interpreting the coefficient for the x-variable, we should test whether the coefficient is statistically significant.

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A regression model may be made more accurate by: Select one: O a. increasing the number of observations O b. using the high-low (2 factor) algorithm O c. re-ordering the data from the lowest Y-value to the highest Y-value O d. setting the intercept as the data's point of origin