True/False 1. Omitting a variable that effects Y always biases or estimate for ß. 2. If the model is stochastic, # y; for every i, SSE is 0 and the R = 1 3. OLS maximizes the Sum of Squared errors.
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![True/False
1. Omitting a variable that effects Y always biases our estimate for B.
2. If the model is stochastic, fi + y for every i, SSE is 0 and the R2 = 1
%3D
3. OLS maximizes the Sum of Squared errors:
4. If our model is biased, Ele|x] 0.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3ab263a9-10a1-4733-9d53-b5fd3e9bb2c5%2F0f3f562b-60ad-483b-aaf4-efb47127d039%2F4gkjzq_processed.jpeg&w=3840&q=75)
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- Is it true of false that the classical errors in variables (CEV) assumption is that the measurement error is correlated with the unobserved true value of the explanatory variable.The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship isS = k (YZ/ P)where k has been estimated (with past data) to equal 100.a. If Y = $11,000, Z = $1,200, and P = $20,000, what value would you predict for S?b. What happens if P is reduced to $17,500?c. How would you go about developing a value for k?d. What are the potential weaknesses of this model?TRUE OR FALSE. A model with heterosdasticity problem most likely has insignificant parameter estimates.
- The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship is S=kYZP where k has been estimated (with past data) to equal 100. If Y=11,000,Z=1,200, and P=20,000, what value would you predict for S? What happens if P is reduced to $17,500? How would you go about developing a value for k? What are the potential weaknesses of this model?If a Winters' model for new car dealer sales, comes up with four seasonal indices with values of Q1 = 0.95, Q2 = 1.04, Q3 = 1.05, and Q4 = 0.96, the following can be interpreted: Multiple Choice Q1 sales are lower because of Q2 sales. Q1 sales are usually about 5 percent below an average quarter. Q1 sales are usually about 5 percent above an average quarter. Q1 sales are higher because of Q2 sales.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?
- Eastman Publishing Company is considering publishing an electronic textbook about spreadsheet applications for business. The fixed cost of manuscript preparation, textbook design, and web site construction is estimated to be $172,000. Variable processing costs are estimated to be $5 per book. The publisher plans to sell single-user access to the book for $42. Through a series of web-based experiments, Eastman has created a predictive model that estimates demand as a function of price. The predictive model is demand = 4,000 − 6p, where p is the price of the e-book. (a) Construct an appropriate spreadsheet model for calculating the profit/loss at a given single-user access price taking into account the above demand function. What is the profit estimated by your model for the given costs and single user access price (in dollars). $ (b) Use Goal Seek to calculate the price (in dollars) that results in breakeven. (Round your answer to the nearest cent.) $ (c) Use a data table that varies…The following ACF plots were produced for raw data of monthly sales of two different variables, A and B. a) Explain which variable is likely to be easier to forecast. b) Explain how your answer to part a) would change if these were residuals of an ARIMA model instead of “raw data of monthly sales”.An independent variable in a model is also called:a. explained variable.b. unexplained variable.c. explanatory variable.d. dependent variable.
- In general, what is true about the relationship between the Sum of Squared Residuals in the restricted and unrestricted model? a. SSRr = R-squared * SSRur b. SSRr < SSRur c. SSRr > SSRur d. SSRr = SSRurSuppose 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 termWhich of the following statements is true? a) None of the other possible answers are true. b) Under the Classical Linear Model assumptions, the OLS estimator has the highest variance among unbiased estimators. c) Taking the natural log of a non-normal distribution often yields a distribution that is closer to normal. d) The Central Limit Theorem (CLT) assumes that the dependent variable is unaffected by unobserved factors. e) The mean of a non-normal distribution is 0 and the variance is σ2.