In the model Yi = b0 + b1*Xi + ui, Xi can take values 1 or 2. If E(ui | Xi = 2) > E(ui | Xi = 1), the OLS estimate of b1 is consistent True False
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- ASSISTANCE REQUIRED FOR PART "e" i- vi ONLY, please. Also can you please show step by step how to get null and alternative in the hypothesis? A car company wants to know the monthly sales made in ($000), based on the brand of vehicle.The data collected was entered on a MINITAB spreadsheet for analysis. Exhibit II below was subsequently generated. Exhibit 2 Model N Mean Median Tri.Mean Std Dev S.E. Mean Hyundai 23 109 135 107.64 * 1.34 Toyota 27 165 124 143.65 9.5 ** a) Determine the values of * and **. b) Give the unbiased point estimate for the average monthly earning from Hyundai Vehicles.c) Give the unbiased point estimate for the variance of monthly earning from Hyundai Vehicles.d) Assuming normality, construct and interpret a 90% confidence interval for the average monthly earning from Toyota Vehicles. e) You are required to test at the 5% level of significance the hypothesis that the average monthly earnings on Hyundai Vehicles is equal to $110,000 versus the…We want to estimate the treatment effect of D ony via a linear regression model y = bo+b1x +rD+u.where x is an exogenous controi variable. If the value of the treatment variable Dis randomly assigned. there O a. the OLS estimate of r is biased due to sample selection. Ob.the OLS estimate ofris unbiased. Oche error u is homoskedastic. Od.the OLS estimator is BLUE.In regression model: Yi = B1+ B2Xi+ Ei, where Ei is a random variable independent of Xi, with mean and variance constant and different from zero. Ei ~(media, varianza) Obtain the OLS estimator of ẞ2. Show that the properties of finite samples hold.
- Describe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?Suppose we estimate the following econometric model with OLS: What does OLS do? OLS chooses and to minimize the sum of residuals. OLS chooses and to minimize the sum of squared residuals. OLS chooses and to minimize the error term OLS chooses and to minimize the error term………. (1) For this model, ESS = 1,740 and TSS = 2,000 Instructions: 1 The value of RSS is …………. 2 The degrees of freedom associated with RSS are …………. 3 The degrees of freedom associated with ESS are ………… 4 The degrees of freedom associated with TSS are ………… 5 The F-test statistic for testing the significance of the above model is ………… 6 The coefficient of determination () for this model is …………
- (look at the attached image) a. Explain whether the specification uses a pre-post or a simple difference method? Discuss the counterfactual in the specification above. b. Using the specification above, discuss whether you would be able to estimate an unbiased estimate on the effect of BSM on students' test scoresYour friend - an artist - has asked you to help her determine how many paintings sized 50x150cm she should paint for sale. She's deciding between one, two, three, or four paintings. Your friend sells the paintings for 300 monetary units each. She spends 8 hours on each painting (1 hour of work = 15 monetary units). Additionally, each painting incurs an extra cost of 40 monetary units (for canvas, backing, paints, brushes, sprays). Based on past data, you estimate that with a probability of 0.2, there will be no potential buyers; with a probability of 0.2, there will be one potential buyer; with a probability of 0.2, there will be two potential buyers; with a probability of 0.3, there will be three potential buyers; with a probability of 0.1, there will be four potential buyers. Assume that if there are fewer paintings produced than potential buyers, some (randomly selected) potential buyers will remain without a painting; otherwise, all potential buyers will purchase exactly one…Q1. State the property of an estimator that gives a correct estimate of the population parameter of interest, but only on average. Q2. State the property of ian estimal or thal converges to the populalion paaameter of interest as the sample size goes to infinity. Q3. Why is an efficient estimator a desirable property of the OLS estimator? Q4. Stare the assumption(s)under the classical linearregression model giving rise to a biased standard error of the coefficient estimates when violated.
- Test whether the slope coefficient in both Model is statistically significant at 10% significance level.The following data gives the experience of the machine operators and their performance ratings as given by the number of good parts turned out per 100 pieces.Experience(X) 16 12 18 4 3 10 5 12Performance Ratings (Y) 88 87 89 68 78 80 75 83Obtain the regression line of performance ratings on experience and estimate the probable performance if the operator has 7 years of experience.A machine is designed to fill toothpaste tubes, on an average, with 5.8 ounces of toothpaste. The manufacturer does not want any underfilling or overfilling. The correct hypotheses to be tested are