A simple regression analysis of a sample of 10 observations resulted in the following information regarding a dependent variable (y) and an independent variable (x). ?X = 90 ?Y = 170 ?(X - X?)Ā² = 234 ?(Y - Y?)(X - X?) = -468 ?(Y - Y?)Ā² = 392 ?(Y - ?)Ā² = 1400 The least squares estimate of b? equals Select one: a. -.334 b. 2 c. -2 d. 0.5
Added by Martin G.
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Step 1: Calculate the least squares estimate of b1 using the formula b1 = Ī£((xi - x)(yi - y)) / Ī£((xi - x)^2) Show moreā¦
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A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). Ī£x = 90 Ī£(y - )(x - ) = 466 Ī£y = 170 Ī£(x - )2 = 234 n = 10 Ī£(y - )2 = 1434 SSE = 505.98 The least squares estimate of the slope or b1 equals a. .923. b. 1.991. c. -1.991. d. -.923.
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A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). Ī£x = 90 Ī£(y - Č³)(x - xĢ) = 466 Ī£y = 170 Ī£(x - xĢ)2 = 234 n = 10 Ī£(y - Č³)2 = 1434 SSE = 505.98 The least squares estimate of the intercept or b0 equals a) -1.991. b) .923. c) -.923. d) 1.991.
Shaiju T.
In exercise $1,$ the following estimated regression equation based on 10 observations was presented. $$y=29.1270+.5906 x_{1}+.4980 x_{2}$$ $\begin{array}{l}{\text { a. Develop a point estimate of the mean value of } y \text { when } x_{1}=180 \text { and } x_{2}=310 \text { . }} \\ {\text { b. Predict an individual value of } y \text { when } x_{1}=180 \text { and } x_{2}=310 \text { . }}\end{array}$
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