log_price = 8.381284 - 0.0107765 mpg + 0.0002239 + 0.0132012 trunk - 0.1232495 headroom
For us to see if headroom and trunk have any effect on price, we look at their P>|t|
For trunk:
Since the probability of rejecting null hypothesis that trunk has no effect on price is 35.6% (which is more than widely accpeted 5% level of significance) we can safely say that trunk has no effect on log_price
For headroom:
Since the probability of rejecting null hypothesis that headroom has no effect on price is 4.6% (which is less than widely accpeted 5% level of significance) we can safely say that headroom has significant effect on log_price
You are given different sets of Stata output below. Please use the appropriate Stata output to...
Given the following regression output in Stata Indicate what is the effect of x2 on Y by testing the hypothesis that x2 determines Y given · regress y xl x2 Source SS dEMS Model Residual 2.6644e+092 1.3322e+09 26878436.6 12 2239869.72 Number of obs = F( 2, 12) = Prob > F R-squared Adj R-squared = Root MSE 15 594.76 0.0000 0.9900 0.9883 1496.6 Total 2.6912e+0914 2.6912 192231167 Coef. Std. Err. t >It (95% Conf. Intervall x1 2.44061 .3440342 -32137.37 6.125326...
Problem.2. Because of economic crisis Darth Vader ordered Data Analysis department of the Empire Inc. to analyze the price factors of Star Fighters of different modifications. Data (N=74 obs) on the ion-fuel-economy (mpi), length, weight of carried laser arm (kg), Twin Ion Engine displacement (cubic cm) and Engine origin ( For Empire Inc., variable Foreign =0) were used to find out how the estimate of the price (SM) of Fighters depends on fuel economy. The results are following: reg price...
The top stata output is a regression on how the sex of a person affects gross weekly pay after the implementation on the equal pay act The bottom stata output is a regression on how the sex of a person affects gross weekly pay before the implementation on the 2010 equal pay How has the gender pay gap change before and after the act? Is the change significant and what assumption justify using Before the act as a control group?...
log type: smcl opened on: 30 Jan 2019, 23:24:04 . use "/Users/br2.dta" . summarize price sqft Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- price | 1,080 154863.2 122912.8 22000 1580000 sqft | 1,080 2325.938 1008.098 662 7897 . correlate price sqft (obs=1,080) | price sqft -------------+------------------ price | 1.0000 sqft | 0.7607 1.0000 . correlate price sqft, covariance (obs=1,080) | price sqft -------------+------------------ price | 1.5e+10 sqft | 9.4e+07...
. There is Stata output from a second OLS regression model with the variables defined as above. This time we include an interaction term "ageXgender" for the independent variables "age" and "gender." Use this output to answer parts g through i. regress casp age gender married agexgender df Number of obs- Source | 4,849 137.04 0.0000 0.1017 0.1009 6.0079 MS +FC4, 4844) 4,844 36.0944447 R-squared Model 19785.9491 4 4946.48728 Prob > F Residual 174841.49 Adj R-squared + Total 194627.439 4,848...
Question 1 First run the regression: EARNINGSi = β1 + β2ASVABCi + β3Si + ui Then run the regression with experience: EARNINGSi = β1 + β2ASVABCi + β3Si + β4EXPi + ui Compare the results from these two regressions, do you get an indication that the previous estimate of schooling without EXP was biased? If so, in which direction? And why is that? Question 2 Add gender dummy variable to the regression (the one running regression of EARNINGS on ASVABC,...
23:01 4G Midterm Econometrics II Semester 1 2.. 1 You are given data on price and quality of cocaine. You believe that the quality of cocaine affects the price, so you ran the following regression: The STATA output storage display valuc name type foemat l label variable label flat %9.0g float %9.0g float %9.0g float %9.0g peice per gram in dollars foe a cocaine number of grams of cocaine in a give quality of the cocaine expressed as a time...