Let sale denote the sale price for a house, sqft its square footage, and days the number of days that it has been on the market. Consider running two differentregressions:First regression: sale = B1 + B2sqft + ß3days + eSecond regression: sale =Bi + B2sqft + eWhich of the following statements is false? In the options below, the quantities SST, SSE, and SSR are as defined when we discussed R?, that is SST = E(Y, – Ỹ)²,SSE = E(Y; - Ý )², and SSR =i=1O a. The SST from the first regression can be strictly smaller than the SST from the second regression.O b. The SSE from the first regression can be strictly smaller than the SSE from the second regression.O c. The R- from the first regression can be strictly larger than the R2 from the second regression.O d. The R2 from the second regression is equal to the R2 from the regression sqft = Yi + Y2sale + eO e. The SSR from the first regression can be strictly larger than the SSR from the second regression.

Answered: First regression: sale = ß1 + B2sqft +…

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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4. Consider the following multiple regression results, where the dependent variable is the number of movie tickets sold per week, X, is the ticket price, and X2 is the cost of DVD rental. -51.0918X¡1 + 41.4607X¡2 (37.0184) (13.130) (0.584) Sp t = (-6.800) SSR = 17,023 SSE = 6,262 = 23,285 SST = п 3D 20 Complete the missing entries in the output. 1 | Are the slope coefficients, b, and b2, individually statistically significant (a = 0.10 2. 3. Calculate the standard error of the regression (s.) and the R2.
Q1. The values of X and Y are given in the following table. X0235 8. Y 157 11 | 17 = 18. Y = 41, xY 222, > x² = 102, > Yy² X = 485 a) Find the Coefficient of Correlation b) Find the Coefficient of Determination and Coefficient of Non-Determination? c) Calculate the line-of-best- t (linear regression line) Ý = a + bX, d) If x = 8, estimate the response y.
4. In multiple regression, why do we prefer our IVs to be uncorrelated with each other (i.e., we want rx, x, to be 0)?
Question 2. Show that, for a simple linear regression, R² = ry, where R² is the coefficient of determination and rxy is the sample correlation between Y and X. Hint: Σ" (Υ - Y)2 Σ1(Y₁-Y)²¹ SxY √SXXSYY' where Sxy = 1 (X; — X)(Y; — Y), Sxx = ₁1(X; - X)², Syy = ₁₁(Y₁ - Y)². R² = "XY =
How would i solve for the tb1
The research hypothesis posits that the treatment association between two variables will be greater than zero (H1: rxy > 0). What would be concluded for r(29) = .267, p > .05?
assessment.casa.uh.edu/Assessment/Root/Pages/TestTaker/Quiz.aspx?id=2F507231-0111-4CFC-8C26-F38ED05C3949 f) O None of the above Review Later Question 7 If the LSRL relating the independent variable x and the dependent variable y for a given problem is ŷ = 2x + 4, then an increase of 1 unit in x is associated with an increase of how many units in y? a) 06 b) 00 d) O1 e) 04 Review Late
D. Only OLS assumption #2 is satisfied. The estimated regression is Y = 39+0.45X; Compute the estimated regression's prediction for the average score of students given 99, 129, or 155 minutes to complete the exam. Given 99 minutes, the estimated regression's prediction for the average score of students is Given 129 minutes, the estimated regression's prediction for the average score of students is Given 155 minutes, the estimated regression's prediction for the average score of students is (Round your responses to two decimal places.) Compute the estimated gain in score for a student who is given an additional 19 minutes on the exam. The estimated gain in score for a student who is given an additional 19 minutes on the exam is (Round your response to two decimal places.) Click to select your answer(s). W (DELL] o search PROU II
4. Suppose that n=100 i.i.d observations for (Y₁, X₁) yield the following results Ỹ = 32.1 +66.8X, SER=15.1, R² = 0.81 (15.1) (12.2) Another researcher is interested in the same regression, but he makes an error when he enters the data in his regression program: He enters each observation twice, so he has 200 observations. Using these 200 observations, what results will be produced by his program? Write it in the following format: Ỹ +---X, SER= (---) (---) R² =
Suppose that n = 100 i.i.d. observations for (Y, X) yield the following regression results: Ŷ 32.1 + 66.8X, SER = 15.1, R² = 0.81. = (15.1) (12.2) Another researcher is interested in the same regression, but he makes an error when he enters the data into his regression program: He enters each observation twice, so he has 200 observations (with observation 1 entered twice, observation 2 entered twice, and so forth). a. Using these 200 observations, what results will be produced by his regression program? (Hint: Write the "incorrect" values of the sam- ple means, variances, and covariances of Y and X as functions of the "correct" values. Use these to determine the regression statistics.) Ŷ - X, SER = 6tc () () b. Which (if any) of the internal validity conditions are violated?
Suppose that n= 195 I.I.d. observations for (Y, X;) yleld the following regression results: v= 32.68 + 67.55Xx, SER= 18.63, R = 0.84 (15.7) (12.5) Another researcher is interested in the same regression, but he makes an error when he enters the data into the regression: He enters each observation twice, so he has 390 observations (with observation 1 entered twice, observation 2 entered twice, and so forth). Which of the following eatimated parameters change result? (Check all that apply) O A. The estimated intercept and slope. O B. The R of the regression. Yc. The standard error of the regrussion (SER). YD. The standard errors of the estimated coefficients. Using the 390 observations, what results will be produced by his regression program? Ý= 32.68 + 67.55X, SER =.R = 0.84 (Round your responses to two decimal places)
A statistics student is asked to estimate Y = Bo + B1X + E. She calculates the following values: Ex = 280, Σ(x₁ - x)² = 350, Σy, = 600, Σ(y, − y) = 1000 Σ(x,x)(y₁ - y) = -630, n = 20 Which of the following is the sample regression equation? OY--55.2-1.8X + e OY 55.2 +1.8X + e OY-55.2+1.8X + e OY 55.2 1.8X + e

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