Use the Stata output below. The data comes from students in an undergraduate economics course. Theregression of interest is:final-Bo + B, atndrte + B,hurte + spriGPA + B, ACT.reg final atndrte hwrte priGPA ACTSourceModelResidualO 4; 669O 5; 669O4; 673O 5; 673O 4: 674O 5; 674finalatndrtehwrtepriGPAACTconsSSTotal 15024.65433094.7077611929.9465df.0138725.01834761.90634739905169.2259084669673Coef. Std. Err..010863375023605353321.46863MS773.67693917.83250622.324895Number of obsF(4, 669)Prob FR-squaredAdj R-squaredRoot MSEt P>|t|===>W=674[95% Conf. IntervallConsider the null hypothesis that all of the slope parameters are equal to zero. What are the numerator anddenominator degrees of freedom?

A regression output is given based on an undergraduate economics course.

Answered: Use the Stata output below. The data…

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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G The following table shows the weights of some persons in kilograms and their heights in centimeters: X Weight (kg) 60 70 59 90 Height (cm) 165 170 144 189 Compute the slop B1 needed for the linear regression equation. Selected Answer: Correct Answer: [None Given] 1.15 + 5%
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A. Give the regression equation in the form y=Asin(B(x-C))+D B. Use the regression equation to predict the average number of daylight hours in February 2017.
Give the equation of the regression line: -913.2969+0.4808years(y) a) Plug an actual x value into the equation and discuss the difference between the real y and the predicted yb) Discuss the domain of your datac) Include the scatterplot with line of best fit
Use the Stata output below. The data comes from students in an undergraduate economics course. The regression of interest is: final =B₁ + B₁ atndrte + ß₂hwrte + Â¸priGPA+ Â¹ ACT .reg final atndrte hwrte priGPA ACT Source Model 3094.70776 11929.9465 Residual Total final SS atndrte hwrte priGPA ACT _cons 15024.6543 df 773.676939 4 669 17.832506 MS 673 22.324895 Coef. Std. Err. .0138725 .0183476 .010863 1.906347 .3750236 .3990516 .0535332 9.225908 1.46863 Number of obs F(4, 669) Prob > F R-squared Adj R-squared Root MSE t P>|t| ||||||||||||| 674 [95% Conf. Interval] Approximate the p-value from the null hypothesis that all of the slope parameters are equal to zero.
Data from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
Find the regression equation Student 1 4 5 6 7 8 9 10 Placement Exam 83 89 92 77 81 81 85 85 87 84 GWA 83 85 90 80 83 85 87 84 90 85 Select the correct response: y=35.39-0.5901x y=35.39x+0.5901 y=0.5901x-35.39 y=35.39+0.5901x 3. 2.
The table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 13 12 11 10 9 a. 15 b. 8 c. 7 d. 20
We conduct a regression of size on hhinc, owner, hhsize1, hhsize2, and hhsize3. Wedo not include the constant. The regression output is reported in Table 3. Would youconclude that the home size increases with the household size? Interpret the signand magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3
Find the new data point (x,y) in which x=2 from the data points (1.3) and (4.12)

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