3. Using multiple linear regression, estimate the values of a, b and c in the given regressionmodel.MODEL: y = axbecxXy13.625.236.848.8

The data set is given as: x y 1 3.6 2 5.2 3 6.8 4 8.8 The equation is given as:…

Answered: 3. Using multiple linear regression,…

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 value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The accompanying data table gives the value and the annual revenue for 15 major sport teams. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. b. Assuming a linear relationship, use the least-squares method to determine the regression coefficients b0 and b1. (Round the value of b0 to the nearest integer as needed. Round the value of b1 to two decimal places as needed.)
Find the multiple regression equation with weight as the response variable and the dummy variable of sex and the variable of age as the explanatory variables.
i. Determine the dependent and independent variable ii. Based on the output, state the simple linear regression model. ii. Interpret the linear regression model obtained in part (b).
The residual plot for a linear regression model is shown below. Assess the fit of the linear model, and justify your answer. The line is a good fit because the points on the residual plot have a clear pattern. The line is a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot have a clear pattern.
At a large state university, the Statistics department is interested in tracking the progress of its students from entry until graduation. In this example: X represents a student’s final numeric grade (out of 100) in an introductory statistics course Y represents a student’s final numeric grade (out of 100) in an upper-level statistics course The least-squares regression equation for this relationship is: Y = 5.20 + 0.93X What is the slope of the regression line? Provide a numeric value as shown in the equation.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.3 8.5 y 13.4 7 3.6 2.6 2.2 2.6 0.8 11 10.2 7.4 6 5.7 6.3 4.9 * = thousands of automatic weapons y = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 10.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 9.9 thousand automatic weapons? Answer = Round to 3 decimal places.
Which of the multivariate regression parameters listed below would be best interpreted as: the proportion of variation in the dependent variable explain by all the independent variables in the model. a b1 X1 R2
The data point height=175 cm, height =80 cm was misrecorded as height=145 cm, height =80 cm. If we use the simple linear regression and do not correct the mistake, what is the impact of this point on the model?
Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|
The President of the Farmers Association wants to know how the amount of fertilizer and theamount of water given to plants affect their growth. The results were inputted into MINITABso as to fit the model. Regression Analysis: Growth versus Water, Fertilizer The regression equation isGrowth = ? + ? Water + ?Fertilizer Predictor Coef SE Coef T PConstant 42.085 ** 3.118 0.009Water 0.178 0.386 0.460 0.654Fertilizer 5.790 0.952 6.083 * S = 6.159 R-Sq = 77.1%% R-Sq(adj) = 73.3% Analysis of VarianceSource DF SS MS F PRegression 2 1532.603 766.301 *** ****Residual Error 12 455. 130 37.928Total 14 1987.733 i Write out the regression equation ii. What is the sample size used in this investigation?…

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3. Using multiple linear regression, estimate the values of a, b and c in the given regression model. MODEL: y = axbecx X y 1 3.6 2 5.2 3 6.8 4 8.8