Consider the Stata estimation output obtained via OLS estimation of the model y; = Bo + Bi + uj, wherey is consumption of litres of beer and x is weather temperature measured in Celsius degrees.SourcedfMSNumber of obs365E(1, 363)178.94Model2325.899612325.8996Prob > E0.0000Residual4718.3944936312.99833190.3302R-squaredAdj R-squaredRoot MSE0.3283Total7044.29409364 19.35245633. 6053consumptionCoef.Std. Err.P>It|[954 Conf. Interval]temperature.7948826.059422613.380.000.6780269.9117382cons8.5289071.2753636.690.0006.02087911.03693Select the correct sentence:O The estimated model is sufficient to prove that higher temperature is the main cause for higher consumption of beerO The regression explains 0.33 % of the total variation in consumption of beerO The estimated model predicts a consumption of 0.79 litres when the temperature is of 1 degree CelsiusIf the sample contains an observationi such that y; =30 and zi =25. then uj1.599028

The regression equation is y^=8.528907+0.7948826x.

Answered: Consider the Stata estimation output…

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 type of casting iron has Hall-Petch parameters: σ0 = 36.3 MPa and K = 6.5 MPa ∙ mm^−0.5. For a given sample, the grain size distribution is shown in the diagram below. Each bar represents the percentage of grains in particular size. First, estimate the average grain size based on concept of “weighted mean” (in case you do not know, search for this term). Then, apply Hall-Petch Equation to calculate the yield stress. (Note: 1 μm = 0.001 mm)
When do we conduct GLS estimation? How does it solve the problems that may arise with OLS estimations?
Assume that ui and µ2 are the averages of maximum speeds of new high-tech electric scooter types. Use the t test at significance level 0.01 to test Ho: µi - µ2 = -18 versus H.: μι - μ2<18 for the following data: ni = 6, x1=117.8, si=5.06, n2 = 6, xz= 128.2, and s2 = 5.28. (where n, , and s denote the sample size, sample mean and sample standard deviation respectively.) %3D
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Ims.tu.edu.sa قائمة القراءة. Remaining Time: 34 minutes, 24 seconds. v Question Completion Status: QUESTION 1 "Suppose X has an exponential distribution with ß=1/2 , then P (X2 2) is " 0.3988 O 0.0183 0.4786 O 0.2916 QUESTION 2 "Suppose X has an exponential distribution with ß=1/4 , then P (Xs1.) is " O 0.9817 O 0.3246 O 0.4105 O 0.5116 QUESTION 3
Climate change and CO2 2011 Data collected fromaround the globe show that the earth is getting warmer.The most common theory relates climate change to anincrease in atmospheric levels of carbon dioxide (CO2),a greenhouse gas. The mean annual CO2 concentration inthe atmosphere (parts per million) is measured at the top of Mauna Loa in Hawaii, away from any local contami-nants. (Available at ftp://ftp.cmdl.noaa.gov/ccg/co2/ trends/co2_annmean_mlo.tx)The mean surface air temperature is recorded as thechange in °C relative to a base period of 1951 to 1980.(Available at data.giss.nasa.gov/gistemp/graphs_v3/)Here are a scatterplot and regression for the years from1959 to 2011:Dependent variable is TempR-squared = 82.3%s = 0.0985 with 53 - 2 = 51 degrees of freedomVariable Coefficient SE(Coeff) t-Ratio P-ValueIntercept -2.98861 0.2086 -14.3 ...0.0001CO2 0.0092 0.0006 15.4 ...0.0001a) Write the equation of the regression line.b) Is there evidence of an association between CO2 leveland global…
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10. You estimated a regression with the following output. Source | SS df MS Number of obs = 333 -------------+---------------------------------- F(1, 331) = 4608.21 Model | 32636494.1 1 32636494.1 Prob > F = 0.0000 Residual | 2344225.8 331 7082.25316 R-squared = 0.9330 -------------+---------------------------------- Adj R-squared = 0.9328 Total | 34980719.9 332 105363.614 Root MSE = 84.156 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 30.79902 .4537022 67.88 0.000 29.90652 31.69153 _cons | 20.85313 42.1964 0.49 0.621 -62.1538 103.8601…
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