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- 3. A Ross MAP team is trying to estimate the revenues of major-league baseball teams during the regular season using a regression model. Currently, the independent variables include stadium capacity, the number of weekend games, the number of night games, and the number of Wins (out of 162 regular season games). One of your team members suggests that the model also should include the number of losses as it provides additional explanatory power. Assume that ties are not possible; so every game results in exactly one team winning and the other team losing. Which of the following statements is the most likely conclusion of the new regression model? (a) R2 will increase, adjusted R2 will decrease, and Serror will decrease. (b) R2 and adjusted R2 will increase, and serror will decrease. (c) R, adjusted R2, and Serror will increase. (d) We cannot trust the regression output as some variables are highly correlated, resulting in multicollinearity. Answer to Question 3:Which of the following is true of fixed effect estimators A. The fixed effects estimator is equal to the instrumental variable estimator if R^2 is equal to 1. B. The fixed effects estimators are biased if the regression model exhibits multicollinearity. C. The fixed effects estimators have lower variance than the ordinary least squares estimators. D. The fixed effects estimators have large standard errors when R^2 lies close to 0.16. A scatterplot of the monthly salary (in thousands of pesos) versus years of education for seven full-time workers is displayed below. The least- squares regression line is drawn on the plot. Six of the data points are plotted with open circles and the seventh is plotted with a solid circle. The data point plotted with a solid circle to 20 Ne stynan eftdutatien A. has a large residual and is influential. B. has a small residual and is influential. C. has a large residual and is not infiluential. D. has a small residual and is not influential. 00 09 oad jo umroy s
- We are planning an experiment comparing three fertilizers. We will have six experimental units per fertilizer and will do our test at the 5% level. One of the fertilizers is the standard and the other two are new; the standard fer- tilizer has an average yield of 10, and we would like to be able to detect the situation when the new fertilizers have average yield 11 each. We expect the error variance to be about 4. What sample size would we need if we want power .9?12 young batsmen practiced batting at the nets for varying periods of time, and their dot ball percentage was calculated at the end of the month: a) Find the relationship between dot ball percentage and practice time per month using a scatter diagram and interpret. b) Find correlation coefficient and comment. c) Fit a least square regression equation (line) of dot ball percentage on practice time per month and comment. d) What will be the dot ball percentage when practice time per month is 32hr? e) Comment on the regression equation and explore how well it fits.For theoretically modelling the economic development of national economy scenarios the following 2 models for GDP increment are analysed: a. Yt = Yt-1 + at b. Yt = 1.097 Yt-1 - 0,97 Yt-2 + at, where Y - GDP increment a - White noise with zero mean and constant variance o2 =100 t- Time (quarters starting with Q1, 1993) Check by an algebraic criterion which one is stationary.
- Which one of the following assumptions is required for the 2SLS estimator to be consistent? a) There are perfect linear relationships among the instrumental variables b) There is a correlation between each instrumental variable and the endogenous variable c) The conditional variance of the error term depends on an exogenous explanatory variable d) There is a strong correlation between each instrumental variable and the error termA BS Agribusiness Management student from UPLB is conducting a Special Problem about the evidence of profitability among SMES in the Philippines. She intends to provide the risk in engaging to SMES which is measured by the variance of the usual daily revenue. If the variance is found to be above 500K pesos, the risk is still high which means a successful business transformation in various dimensions of their operations must be done (e.g. spanning enhanced entrepreneurial skill, innovation in process and product development, more successful collaboration across SMES and with larger firms, and improved crisis resilience among other factors) through a seminar to be supported by the different government agencies. R COMMANDER OUTPUT One sample Chi-squared test for variance data: daily_revenue x-squared = 389.18, df = 22, p-value < 2.2e-16A researcher investigates whether cold medication effects mental alertness. It is known that scores on a standardized test containing a variety of problem-solving tasks are normally distributed with = 64 and = 8. A random sample of n = 16 teenage and a sample of n = 25 adults are given the drug and then tested. On average, the teenagers scored and average of ? = 58 and the adults scored and average of M = 65.5.a. Are the data sufficient to conclude that the medication significantly reduces mental alertness in teenagers? Test with = .01.b. Are the data sufficient to conclude that the medication significantly increases mental alertness in adults? Test with = .01.
- It is hypothesized that the total sales of a corporation should vary more in an industry with active price competition than in one with duopoly and tacit collusion. In a study of the merchant ship production industry it was found that in 4 years of active price competition, the variance of company A’s total sales was 114.09. In the following 7 years, during which there was duopoly and tacit collusion, this variance was 16.08. Assume that the data can be regarded as an independent random sample from two normal distributions. 1. Test, at the 5% level, the null hypothesis that the two population variances are equal against the alternative that they are not equal.Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certain