- Based on the multiple regression model, does demand for beef respond significantly to price of pork? Why?
Homework Answers
Yes. Demand for beef respond significantly to the price of pork.
If Ho: B =0
H1: B not equal to 0
(Where B = coefficient of ppork)
Then,
t value of coefficient of ppork is 3.53 . At 5% significance level, we can reject Ho. So, ppork has significant effect on the demand for beef.
Moreover, p value is 0.004 which means we can reject null hypothesis at minimum 0.4% significance level which also indicates significance of demand for beef in response to change in the price of pork.
Add Answer to:
Based on the multiple regression model, does demand for beef
respond significantly to price of pork?...
What does the coefficient estimate for lnNumHH tell you? Do you think there is a problem...
What does the coefficient estimate for lnNumHH tell you?
Do you think there is a problem with the regression, if so what
is the problem?
• regress lnMedInc in NumHH Source SS df MS Model Residual 1.92343603 8.48203352 1 364 1.92343603 02330229 Number of obs F(1, 364) Prob > F. R-squared Adj R-squared Root MSE IL L LLLL 366 82.54 0.0000 0.1848 0.1826 . 15265 Total 10.4054695 365 .028508136 InMedInc Coef. Std. Err. t P> [t] [95% Conf. Interval] InNumHH...
What does the R2 tell us about the reliability of the results? Does the model explain...
What does the R2 tell us about the
reliability of the results? Does the model explain a large fraction
of the variance in LVRs across the sample?
Source df MS Number of obs - 1,716 17.27 0.0000 0.0661 0.0623 1652 F (7, 1708) Model 3.2992079 7 .471315415 ProbE Residual 46.6103775 1,708 .027289448 R-squared Adj R-squared = Total 49.9095854 1,715 .029101799 Root MSE lvr Coef Std. 2rr. [95% Conf. Interval] -.007698 0000835 0001327 -.0163009 0428063 026664 0045128 6569055 0016265 0000343 0000678...
In the solution proposal DF = 21 when testing this hypotheses, but when doing a f test for significant regression DF is 24. I need help understanding this:) Regards Richard df MS Source I Number of o...
In the solution proposal DF = 21 when testing this hypotheses,
but when doing a f test for significant regression DF is 24.
I need help understanding this:)
Regards Richard
df MS Source I Number of obs 27 2. 24) - 200.25 - 0.0000 О. 9435 Adj R-squared 0.9388 .18837 2 7.10578187 Residual! .85163374 24.035484739 Model 14.2115637 Prob F R-squared Total 15.0631975 26.57935375 Root MSE Coef. Std. Err. [95% Conf. Interval] 125954 085346 .326782 1nLI.6029994 1nK I.3757102 cons1.170644 2.790.000 4.40...
please interpret the regress result findings (sign, coefficient, statistical significance, R^2, Adjusted R^2) for each independent...
please interpret the regress result findings (sign, coefficient,
statistical significance, R^2, Adjusted R^2) for each independent
variable in the NBA salary model
regress salary laggaterevenue lagwp48 Source SS df MS Model Residual 1.1647e+15 8.0148e+15 2 423 5.8236e+14 1.8947e+13 Number of obs F(2, 423) Prob > F R-squared Adj R-squared Root MSE 426 30.74 0.0000 0.1269 0.1228 4.4e+06 = Total 9.1795e+15 425 2.1599e+13 = salary Coef. Std. Err. t P>|t| [95% Conf. Interval] laggaterevene lagwp48 _cons .0044275 1.34e+07 3448595 .0109924 1732419...
Given the following regression output in Stata Indicate what is the effect of x2 on Y...
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...
1) Using the table below, complete the questions that follow (econometrics) a) Using the table above,...
1) Using the table below, complete the questions that follow
(econometrics)
a) Using the table above, which coefficients are statistically
significant? And is the model significant?
b) Give me the equations to calculate the following a t-stat, an
f-stat, coefficient in an SLR, and a Standard Error.
c) What are the 6 Gauss-Markov Assumptions and what, when met,
do they say about our linear model.
d) What is the t-stat for a 95% confidence interval, with 522
degrees of freedom?...
Question 1 First run the regression: EARNINGSi = β1 + β2ASVABCi + β3Si + ui Then...
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,...
Model 1: You are undecided about whether to include education (educ) and gender (male) as controls....
Model 1:
You are undecided about whether to include education (educ) and gender (male) as controls. The output from a regression where you exclude education and gender is shown below: MODEL 2: affair бо + 6,relig = reg affair relig df SS MS Number of obs 601 Source F (1, 599) 10.31 Model Residual| Prob > F 0.0014 1.90494147 1.90494147 599 0.0169 110.657455 184736986 R-squared Adj R-squared 0.0153 = Total 112.562396 600 .187603993 .42981 Root MSE Interval] affair Coef Std....
Interpret the coefficient on logged real gasoline price (lnP) in terms of the sign, magnitude and...
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
This question refers to the question 1 in Exam 1 e sleep and totwork (total work) is measured in ...
This question refers to the question 1 in Exam 1 e sleep and totwork (total work) is measured in minutes per week and educ and age aremeasured in years, male is a dummy variable (male- 1 if the individual is male, and o if female) This is the STATA output of the model: 706 19.59 0.0000 0.1228 Adj R-squared0.1165 df MS Number of obs Model Residual 17092058.5 122147777 F (5, 700) 5 3418411.71 Prob>F 700 174496.825 R-squared Total 139239836 705...
What does the coefficient estimate for lnNumHH tell you?
Do you think there is a problem with the regression, if so what
is the problem?
• regress lnMedInc in NumHH Source SS df MS Model Residual 1.92343603 8.48203352 1 364 1.92343603 02330229 Number of obs F(1, 364) Prob > F. R-squared Adj R-squared Root MSE IL L LLLL 366 82.54 0.0000 0.1848 0.1826 . 15265 Total 10.4054695 365 .028508136 InMedInc Coef. Std. Err. t P> [t] [95% Conf. Interval] InNumHH...
What does the R2 tell us about the
reliability of the results? Does the model explain a large fraction
of the variance in LVRs across the sample?
Source df MS Number of obs - 1,716 17.27 0.0000 0.0661 0.0623 1652 F (7, 1708) Model 3.2992079 7 .471315415 ProbE Residual 46.6103775 1,708 .027289448 R-squared Adj R-squared = Total 49.9095854 1,715 .029101799 Root MSE lvr Coef Std. 2rr. [95% Conf. Interval] -.007698 0000835 0001327 -.0163009 0428063 026664 0045128 6569055 0016265 0000343 0000678...
In the solution proposal DF = 21 when testing this hypotheses,
but when doing a f test for significant regression DF is 24.
I need help understanding this:)
Regards Richard
df MS Source I Number of obs 27 2. 24) - 200.25 - 0.0000 О. 9435 Adj R-squared 0.9388 .18837 2 7.10578187 Residual! .85163374 24.035484739 Model 14.2115637 Prob F R-squared Total 15.0631975 26.57935375 Root MSE Coef. Std. Err. [95% Conf. Interval] 125954 085346 .326782 1nLI.6029994 1nK I.3757102 cons1.170644 2.790.000 4.40...
please interpret the regress result findings (sign, coefficient,
statistical significance, R^2, Adjusted R^2) for each independent
variable in the NBA salary model
regress salary laggaterevenue lagwp48 Source SS df MS Model Residual 1.1647e+15 8.0148e+15 2 423 5.8236e+14 1.8947e+13 Number of obs F(2, 423) Prob > F R-squared Adj R-squared Root MSE 426 30.74 0.0000 0.1269 0.1228 4.4e+06 = Total 9.1795e+15 425 2.1599e+13 = salary Coef. Std. Err. t P>|t| [95% Conf. Interval] laggaterevene lagwp48 _cons .0044275 1.34e+07 3448595 .0109924 1732419...
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...
1) Using the table below, complete the questions that follow
(econometrics)
a) Using the table above, which coefficients are statistically
significant? And is the model significant?
b) Give me the equations to calculate the following a t-stat, an
f-stat, coefficient in an SLR, and a Standard Error.
c) What are the 6 Gauss-Markov Assumptions and what, when met,
do they say about our linear model.
d) What is the t-stat for a 95% confidence interval, with 522
degrees of freedom?...
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,...
Model 1:
You are undecided about whether to include education (educ) and gender (male) as controls. The output from a regression where you exclude education and gender is shown below: MODEL 2: affair бо + 6,relig = reg affair relig df SS MS Number of obs 601 Source F (1, 599) 10.31 Model Residual| Prob > F 0.0014 1.90494147 1.90494147 599 0.0169 110.657455 184736986 R-squared Adj R-squared 0.0153 = Total 112.562396 600 .187603993 .42981 Root MSE Interval] affair Coef Std....
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
This question refers to the question 1 in Exam 1 e sleep and totwork (total work) is measured in minutes per week and educ and age aremeasured in years, male is a dummy variable (male- 1 if the individual is male, and o if female) This is the STATA output of the model: 706 19.59 0.0000 0.1228 Adj R-squared0.1165 df MS Number of obs Model Residual 17092058.5 122147777 F (5, 700) 5 3418411.71 Prob>F 700 174496.825 R-squared Total 139239836 705...
Most questions answered within 3 hours.
-
An MNE is this kind of industry when competition in one country
is essentially independent of...
asked 1 hour ago -
. For this set of questions, determine what
proportion of a normal distribution is located betweeneach...
asked 1 hour ago -
A college student is employed as a door-to-door newspaper
salesman. Historical data suggests that the student...
asked 2 hours ago -
MATLAB HW 11 problem using Switch Case and Input commands
Write a script file that calculates...
asked 2 hours ago -
Considering gravitational time dilation, calculate the time that
passes in Earth’s surface while 1 hour passes...
asked 3 hours ago -
Minitab Problem: Take the Lake Hume June rainfall data and find
use the processes outlined in...
asked 3 hours ago -
X Company is trying to decide whether to continue using old
equipment to make Product A...
asked 3 hours ago -
IN PYTHON ONLY !! Program 2: Re-work
program #5 (WeeklyHours) from the previous assignment such that...
asked 4 hours ago -
The average length of time between arrivals at a turnpike
toll-booth is 26 seconds. What is...
asked 6 hours ago -
(a) A piston at 6.1 atm contains a gas that occupies a volume of
3.5 L....
asked 7 hours ago -
Please answer true or false. Words
cannot be changed or added in to make it true...
asked 7 hours ago -
An empty test tube weighs 15.923 grams. Then,
MgCl2•6H2O is added into the test tube. After...
asked 7 hours ago