Q:obtcain the linear rgression modelfor the following system9 = 2 X, - 3 x, +pr noiseXiE (-5,5),PE(-0.5,05)

The provided system: and .The linear regression model for the given system needs to be determined.

Answered: Q: obtain the linear regression model…

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 table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. D New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. 12²=0 (Round to three decimal places as needed.) 1
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
A family would like to build a linear regression equation to predict the amount of grain harvested per acre of landon their farm. They subdivide their land into several smaller plots of land for testing and would like to select anexplanatory variable they can control. Which of the following is an appropriate explanatory variable that the familycould use to create a linear regression equation? (A) (B) (C) (D) (E) The total amount of rainfall recorded at their farmThe type of crop planted in the plot the previous yearThe average daily temperature at their farmThe variety of grain planted in the plotThe amount of fertilizer applied to each plot of land Why is it that the correct answer is letter E? Why not D? Please explain to me the reason for other choices to be wrong. Thanks!
Consider the linear regression model Y; = Bo + B1 X¡ + U¡ for each i in $10,000) and Y; represents the home size (measured in square feet). We run an OLS regression and get: 1,..., n withn = 1,000. X; represents the annual income of individual i (measured Bin = 43.2, SE(§ „) = 10.2, Bon = 700, SE(Bom) = 7.4. Suppose that we want to test Ho : B1 O against H1 : ß1 # 0 at 1% significance level. Assuming that the sample size is large enough, which one of the following is true about the p-value of this test? 43.2 The p-value can be computed as P(-| ), where is the standard Normal CDF 10.2 а. b. None of the answers 43.2 The p-value can be computed as (- ), where O is the standard Normal CDF 10.2 С. 43.2 d. The p-value can be computed as 20(-- ), where O is the standard Normal CDF 10.2
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.493x - 83.403. Complete parts (a) and (b) below. A Average Weekly Wages (state), x Average Weekly Wages (federal), y 764 1003 766 1048 791 1119 (a) Find the coefficient of determination and interpret the result. r² = 0 (Round to three decimal places as needed.) 800 1152 843 1201 887 1250 924 1277 939 1306
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
Jackson finds that the heavier a person is, the higher his pulse rate tends to be. A linear regression model he built suggests that 20-kilogram differences in weight correspond to differences in pulse rate of 5 beats per minute. Which of the following must be true and explain your answer. (I) The correlation coefficient between body weight and pulse rate is 1/4. (II) Your pulse rate slows down 3 beats per minute if your weight decreases by 12 kilograms.
Which of the following equations represents a simple linear regression line that passes through the origin? a.y=Bx+E b. Y=Bo+Bx-E c. Y=Bo+Bjlog x+Bzlog x2+E Y=8,+6x+B,x B3x,x2 +€
An oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/s
Find the quadratic regression curve through the following points (2, 5), (3, 5), (5, 3) y = 3.0000x? 0.3333x + 1.6667 y = 3.0000x2 + 1.6667x – 0.3333 O y = -0.3333x2 + 1.6667x + 3.0000 O y = 1.6667x2 – 0.3333x + 3.0000

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Q: obtain the linear regression model for the following system y = 2 x₁ = 3 x ₂ +pr noise Xi€ (-5,5), PE (-0.5, 0.5)