Problem 2. [SW 14.9]You have a sample of size n = 1 with data y₁ = 2 and x₁ = 1. You are interested in the value of3 in the regression Y = XB+ u. (Note there is no intercept.)(a) Plot the sum of squared residuals (y₁ - bx₁)² as function of b.Use the range x₁ € [−2,5] foryour plot, and combine all plots of this exercise in one figure. (Use any software you prefer.Excel is one option.)(b) Show that the least squares estimate of 3 is BOLS = 2.(c) Using ARidge = 1, plot the Ridge penalty term ARidgeb² as a function of b.

The linear regression model is Y=Xβ+u The size of the sample is 1, with the sample value being y1=2…

Answered: You have a sample of size n = 1 with…

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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A set of n =25 pairs of scores (X and Y values) produces a regression equation of Ŷ = 3X – 6. Find the predicted Y value for each of the following X scores: 0 = 1 = 3 = -3 =
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…
A regression was run to determine if there is a relationship between hours of study per week (z) and the final exam scores (y). The results of the regression were: y=ax+b a=6.578 b-20.35 r-0.3721 r=0.61 Use this to predict the final exam score of a student who studies 7 hours per week, and please round your answer to a whole number.
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a)x= 140 cm (b)x= 172 cm (c) x = 164 cm (d) x = 158 cm Click the icon to view the table of lengths and girths. The equation of the regression line is y=x+7 (Round to two decimal places as needed.). 4
Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 0.25
Interpret the intercept and the coefficients of D1 and D2 in the regression above.
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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.
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x= 10 wins (c) x=21 wins (d) x= 15 wins The equation of the regression line is y = x+ | (Round to two decimal places as needed.) !!
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