Consider the linear model y =B,+B,x+B,x,+B*3,+B,*+u; You estimate the model y =,+B,x+Bx,+u,observations and obtain the OLS residuals You then estimate the auxiliary regression i =Y,+Y,x+Y,x2,+Y*3+Yq*4+based on 1231 li3 3iThe LM statistic3* 3i+v .i11you obtain to test the null hypothesis that HB,=B,=0 is 20.91. What is the R2 of the auxiliary regression?It is not possible to sayO 0.170.175714O 0.177203

Given Number of observations is 123. The LM Statistic to test the null hypothesis that H0 : β2=β4=0…

Answered: Consider the linear model y =ß,+B,x,…

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter5: Inner Product Spaces

Section5.CR: Review Exercises

Problem 62CR

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Consider the fitted values from a simple linear regression model with intercept: yˆ = 5 + 6x. Assume that the total number of observations is n = 302. In addition, the R-squared of the regression is R2 = 0.6 and Pn i=1(xi − x¯) 2 = 15, where ¯x is the sample mean of x. Under the classical Gauss-Markov assumptions, a) What is the standard error of the estimated slope coefficient?
Find the least-squares regression line y^ =b0+b1x through the points (−2,0),(2,6),(5,14),(8,20),(10,26) and then use it to find point estimates y^ corresponding to x=1 and x=8. For x=1, y^ =? For x=8, y^ =?
Based on a sample on n observations, (x1, y1 ), (x2, y2 ), c, (xn, yn), the sample regression of y on x is calculated. Show that the sample regression line passes through the point (x = x̄, y = ȳ), where x̄ and ȳ are the sample means.
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. The equation of the regression line is y=32.824x+17,659.242. Issues, x 418 475 683 477 492 379 59 51 196 154 Proceeds, y 17,703 28,601 43,966 31,686 36,833 36,916 21,908 10,311 31,407 28,337 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. We can be 95% confident that when there are 646 issues, the proceeds will be between $____ and $____. B. There is a 95% chance…
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 569.The equation of the regression line is y=32.409x+17,285.501. Issues, x 410 467 679 499 497 394 62 53 189 174 Proceeds, y 18,223 28,066 43,757 31,337 35,488 35,312 22,180 10,660 30,384 28,416 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 569. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. There is a 95% chance that the predicted proceeds given 569 issues is between $____ and $____. B. We can be 95% confident…
Consider the points in the plane: (1,2) (2,3) (3,5) (4,4) (5,7) (7,8) (i) Compute the correlation coefficient. (ii) Compute the equation for the regression line.
Draw the scatter plot and compute the predicted equation of the line using the least square Regression line method.Show all the steps, do not just write the answer. X 0 1 3 4 7 Y 7 5 4 3 2 A dice is rolled 3 times, compute the probability of getting AT LEAST ONE 5?
Find the least linear regression of (1, 0), (3, 3), and (5, 6)
Consider the fitted values from a simple linear regression model with intercept: yˆ = 5 + 6x. Assume that the total number of observations is n = 302. In addition, the R-squared of the regression is R2 = 0.6 and Pn i=1(xi − x¯) 2 = 15, where ¯x is the sample mean of x. Under the classical Gauss-Markov assumptions standard error of the estimated slope coefficient = 0.0365 What is the value of the t-statistic for the null hypothesis H0 : the slope coefficient is equal to 0 versus H1 : the slope coefficient is different from 0?
Find the least-squares regression line y^ =b0+b1xy^=b0+b1x through the points (−3,1),(1,8),(6,13),(7,18),(12,27). For what value of is y^ =0? x =?
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings(in millions) are shown in the table. The equation of the regression line is y=47.538x+18,727.65. Complete parts a and b. Issues, x Proceeds, y 423 18,632 460 27,913 687 44,071 485 32,435 500 66,634 389 66,734 57 22,180 65 11,296 188 31,929 163 27,891 (a) Find the coefficient of determination and interpret the result. How can the coefficient of determination be interpreted? (b) Find the standard error of estimate se and interpret the result. How can the standard error of estimate be interpreted?

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