Question

Suppose you are given the following simple dataset, regress Y on X: y=β0+β1x+u X Y 1...

Suppose you are given the following simple dataset, regress Y on X: y=β0+β1x+u

X

Y

1

2

2

4

6

6
  1. Calculate β0 andβ1Show algebraic steps.
  2. Interpret β0 and β1
  3. Calculate the predicted(fitted)value of each observation
  4. Calculate the residual ofeach observation
  5. When x=3, what is the predicted value of Y?
  6. Calculate SSR, SST, and then SSE.
  7. How much of the variation in Y is explained by X?

8)Calculate the variance estimator

Business   Economics   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Suppose y is determined by the true model y=β0+β1x+β2z+ε, and that β2 >0 and COV(z,x) <...
Suppose y is determined by the true model y=β0+β1x+β2z+ε, and that β2 >0 and COV(z,x) < 0. If someone were interested in estimating β1, and did so by using OLS to estimate y = β0 + β1x + u, would the OLS estimator of β1 be biased or not? If it is unbiased, explain why. If it is biased, is the bias positive or negative? Why?
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the OLS estimator will be biased and all further inference like Hypothesis test and Confidence interval will be invalid. In presence of such violation, we can go to Instrument variable estimation/regression method to rebuild the valid empirical study. Assume there is a “good” instrument variable Z for X. (1) How would you argue this is a valid instrument variable?(Hint: validity condition and relevance condition) (2)...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the...
Model: Y = β0 + β1X + u If E(u|X) 6= 0, then we know the OLS estimator will be biased and all further inference like Hypothesis test and Confidence interval will be invalid. In presence of such violation, we can go to Instrument variable estimation/regression method to rebuild the valid empirical study. Assume there is a “good” instrument variable Z for X. (1) How would you argue this is a valid instrument variable?(Hint: validity condition and relevance condition) (2)...
Suppose the joint probability distribution of X and Y is given by the following table. Y=>3...
Suppose the joint probability distribution of X and Y is given by the following table. Y=>3 6 9 X 1 0.2 0.2 0 2 0.2 0 0.2 3 0 0.1 0.1 The table entries represent the probabilities. Hence the outcome [X=1,Y=6] has probability 0.2. a) Compute E(X), E(X2), E(Y), and E(XY). (For all answers show your work.) b) Compute E[Y | X = 1], E[Y | X = 2], and E[Y | X = 3]. c) In this case, E[Y...
8. Calculating SSR, SSE, SST, and R-squared Suppose you are interested in studying the effects of...
8. Calculating SSR, SSE, SST, and R-squared Suppose you are interested in studying the effects of education on wages. You gather four data points and use ordinary least squares (OLS) to estimate the following simple linear model: wage=β0+β1educ+u where wage = hourly wage in dollars educ = years of formal education After running your regression, you decide to examine how the fitted values of wages from your regression compare to the actual wages in your data set. These data are...
Consider the following set of ordered pairs. x 4 1 2 5 y 5 1 3...
Consider the following set of ordered pairs. x 4 1 2 5 y 5 1 3 6 ​ a) Calculate the slope and​ y-intercept for these data. ​ b) Calculate the total sum of squares​ (SST). ​c) Partition the sum of squares into the SSR and SSE.
A sales manager collected the following data on x = years of experience and y =...
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is ŷ = 82 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 1 1 80 2 3 97 3 4 102 4 4 107 5 6 103 6 8 101 7 10 119 8 10 128 9 11 127 10 13 136 (a) Compute SST, SSR, and SSE. SST = SSR = SSE...
You are given the following partial Stata output: regress y x z Source | SS df...
You are given the following partial Stata output: regress y x z Source | SS df MS -------------+--------------------------------------- Model | 810                  1                                Residual |         270               19 -------------+---------------------------------------- Total |     1080                    20 ------------------------------------------------------------------------------ y |     Coef. Std. Err. t P>|t| [95% Conf. Interval] ------------------------------------------------------------------------------   x| 9 1.5   z| 6 3.0 Number of obs = 21 F( 2, 18) = Prob > F = R-squared = Adj R-squared = Root MSE = Fill out all the remaining entries in this Stata output....
1. Given the following observations of quantitative variables X and Y: x= 0, 1, 2, 3,...
1. Given the following observations of quantitative variables X and Y: x= 0, 1, 2, 3, 15 y= 3, 4, 6, 10, 0 a. Make a scatterplot of the data on the axes. Circle the most influential observation. (4 points)    (b)   Determine the LSRL of Y on X. Draw this line carefully on your scatterplot. (4 points) (c)   What is the definition of a regression outlier? (4 points) (d) Which data point is the biggest regression outlier? (4 points)...
The following table is the output of simple linear regression analysis. Note that in the lower...
The following table is the output of simple linear regression analysis. Note that in the lower right hand corner of the output we give (in parentheses) the number of observations, n, used to perform the regression analysis and the t statistic for testing H0: β1 = 0 versus Ha: β1 ≠ 0.   ANOVA df SS MS F Significance F   Regression 1     61,091.6455 61,091.6455 .69        .4259   Residual 10     886,599.2711 88,659.9271      Total 11     947,690.9167 (n = 12;...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT