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- A large school district is reevaluating its teachers' salaries. They have decided to use regression analysis to predict mean teacher salaries at each elementary school. The research has come up with the following prediction equation: Y = $18012.24 + 1432.37X1 - 4.07 X2 where X1 = Yrs Exp and X2 = Yrs Exp2 (a) If a teacher has 7 years of experience, what is the expected salary? (b) If teacher has 10 years of experience, what is the expected salary?The management of a large firm would like to know something about employee morale and the other variables to which it may be related. To study these relationships, each employee in a simple random sample of 27 employees is interviewed and tested to obtain information concerning morale level and the average number of satisfying extra work social contacts experienced during a week. Whether or not the duties the employee usually performs are appropriate to the job title is also determined. The dependent variable Y is measure of morale, the quantitative independent variable, X1 is average number of social contacts, and the following dummy variable coding is used to quantify the qualitative variable: X2 = 1 if yes, X2 = 0 if no. The model including dummy variable and the interaction term was being estimated and a part of computer outputs is below: beta std error t p-value 95% CI for B Lower bound Upper bound Constant 260 134.308…Suppose that the following binary dependent models. The model is based on the driving test of the 400 randomly selected driver’s license applicants. Y=1 if passed the test, or 0 otherwise, and X1 is years of experiences, X2 is the years of educations. Logit: P(Y=1/X) = F(0.563+ 0.040X1+ 0.057X2) What are the probabilities of passing the test for a person with 10 years of experiences and 10 years of educations in each model?
- In the December, 1969, American Economic Review (pp. 886-896), Nathanial Leff reports thefollowing least squares regression results for a cross section study of the effect of age composition onsavings in 74 countries in 1964:log S/Y = 7.3439 + 0.1596 log Y/N + 0.0254 log G - 1.3520 log D1 - 0.3990 log D2 (R2= 0.57)log S/N = 8.7851 + 1.1486 log Y/N + 0.0265 log G - 1.3438 log D1 - 0.3966 log D2 (R2= 0.96)where S/Y = domestic savings ratio, S/N = per capita savings, Y/N = per capita income, D1 = percentage ofthe population under 15, D2 = percentage of the population over 64, and G = growth rate of per capitaincome. Are these results correct? Explain..Which of the following is true of heteroskedasticity? a) The R-squared statistic is affected by the presence of heteroskedasticity b) Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators c) The OLS estimators are not the best linear unbiased estimators if heteroskedasticity is present d) It is not possible to obtain F statistics that are robust to heteroskedasticity of an unknown formSuppose you run the following regression: outcome=alpha0 + alpha1*female + alpha2*married + epsilon. You know that female equals 1 for females and 0 otherwise. You know that married equals 1 if the person is married and 0 otherwise. What is the estimated outcome for non-married females?
- 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.Suppose in period 0 an industry comprises 24 equal-sized firms, each with sales of £12 millions. The assumed random growth process is as follows: in any subsequent year, each firm has an equal chance of either doubling or halving its sales. (In other words, 50% of the firms will increase their sales and 50% will decrease their sales.). Show the validity of Gibrat’s law, using both CR8 and HHI indices after 2 periods.Suppose you run the following regression: outcome=alpha0 + alpha1*female + alpha2*married + epsilon. You know that female equals 1 for females and 0 otherwise. You know that married equals 1 if the person is married and 0 otherwise. What is the estimated outcome for married respondents who are not female?
- What is the index formulation used for?Suppose you run the following regression: outcome=alpha0 + alpha1*female + alpha2*married + epsilon. You know that female equals 1 for females and 0 otherwise. You know that married equals 1 if the person is married and 0 otherwise. What is the estimated outcome for married females?As a manager of a small software retailing company, you are concerned with projected profit next year. While profit can be determined as the difference between sales and maintenance cost, or in symbols, P = S - M, where P is profit, S is sales, and M is maintenance cost including technical support. It is argues that when sales goes up so does maintenance cost because the cost of technical support will go up. Further, it is measured that the correlation between S and M is 0.8. Now given the figure that sales next year is expected to be $300 thousand with standard deviation of $4 thousand and maintenance cost is expected to be $150 thousand with standard deviation of $6 thousand, what would be the expected profit and its standard deviation you will include in your report?