Consider the regression model Yi = β0 + β1X1i + β2X2i + ui. Transform the regression so that you can use a t-statistic to test a) β1=β2. b) β1+aβ2=0. c) β1 + β2 = 1.
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Consider the regression model Yi = β0 + β1X1i + β2X2i + ui. Transform the regression so that you can use a t-statistic to test
a) β1=β2.
b) β1+aβ2=0.
c) β1 + β2 = 1.
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- In a study it was shown that for a sample of 353 college faculty, the correlation was 0.11 between annual raises and teaching evaluations. What would be the coefficient of determination of a regression of annual raises on teaching evaluations for this sample? Interpret your result.Consider a regression in which a coefficient suffers from downward omitted variable bias. If you add a regressor that controls for the omitted variable bias: Group of answer choices 1. Can’t determine 2. The new estimate will be smaller. 3. The new estimate will remain unchanged. 4. The new estimate will be largerShow the graphical form of the econometric error using sample regression line (SRL) and the population regression line(PRL).
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- Imagine that you first estimate an OLS regression with a random sample of 100 observations and then re-estimate the same regression with 100 additional observations which are also randomly sampled. What would you expect to happen as the sample size increases? a. standard error decreases b. R-squared increases c. 95 percent confidence intervals get wider d. Sum of squared residuals decreasesUsing the regression results in column (1):a. Is the college–high school earnings difference estimated from thisregression statistically significant at the 5% level? Construct a 95%confidence interval of the difference.b. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the differenc(answer for me part please)Suppose you have the following data: X Y 3 9 7 45 5 25 2 8 Using OLS methods: estimate the following regression model: Sq root of Yi = Beta0 + Beta1(Xi) + error
- Test whether the slope coefficient in both Model is statistically significant at 10% significance level.Suppose you run a regression y=alpha + beta*x + u. You know that the estimated coefficient is 2.94 and the standard error is 1.09. What is the value of t-statistic for your estimated coefficient beta?Consider the regression model Yi = β0 + β1Xi + ui.a. Suppose you know that β0 = 0. Derive a formula for the least squaresestimator of β1.b. Suppose you know that β0 = 4. Derive a formula for the least squaresestimator of β1?