5. Provide a brief discussion with supporting evidence to the following inquiry: With the responsibility of overseeing career development processes, how does management equip employees with skills that impact their performance in an efficient and effective manner?

## 5. Provide a brief discussion with supporting evidence to the following inquiry: With the responsibility of overseeing career development processes, how does management equip employees with skills that impact their performance in an efficient and effective manner?

Career development can facilitate we attain superior contentment and accomplishment. … Read More...
University of California, Los Angeles Department of Statistics Statistics 100C Instructor: Nicolas Christou Homework 4 Exercise 1 Consider the following simple regression model yi = 0 + 1xi + i, for which E(i) = 0, E(ij) = 0 for i 6= j, and var(i) = 2. The normal equations discussed earlier in class are: n^ 0 + ^ 1 Xn i=1 xi = Xn i=1 yi ^ 0 Xn i=1 xi + ^ 1 Xn i=1 x2i = Xn i=1 xiyi In matrix form this system of two equations with two unknowns can be expressed as follows:  n Pn i=1 P xi n i=1 xi Pn i=1 x2i  ^ 0 ^ 1  =  Pn i=1 P yi n i=1 xiyi  a. Use matrix algebra to nd the solution for the vector ^ = ( ^ 0; ^ 1)0. b. Use matrix algebra to nd the variance covariance matrix of the vector ^ , i.e.  var( ^ 0) cov( ^ 0; 1) cov( ^ 1; 1) var( ^ 1)  : Exercise 2 Consider the following simple regression model for which i  N(0; ). y1 = 0 + 0:5 1 + 1 y2 = 0 ? 1 + 2 y3 = 0 + 0:5 1 + 3 a. Write the above model in matrix form. b. Find the least squares estimates using vectors and matrices. c. Find the variance-covariance matrix of ^ . d. Find the hat matrix. Verify that the sum of the diagonal elements of the hat matrix is equal to 2 ( Pn i=1 hii = k + 1). e. Generate your own data with n = 3 based on this model and verify that the estimates of 0 and 1 are those given by part (b). Exercise 3 Suppose that you need to t the multiple regression model yi = 0 + 1x1i + 2x2i + i, where E(i) = 0, E(ij) = 0 for i 6= j, and var(i) = 2, to the following data: y x1 x2 -43.6 27 34 3.3 33 30 -12.4 27 33 7.6 24 11 11.4 31 16 5.9 40 30 -4.5 15 17 22.7 26 12 -14.4 22 21 -28.3 23 27 It turns out that (X0X)?1 = 0 @ 1:97015 ?0:05623 ?0:01572 ?0:05623 0:00289 ?0:00091 ?0:01572 ?0:00091 0:00174 1 A and X0Y = 0 @ ?52:3 ?1076:3 ?2220:2 1 A a. Find the least squares estimator of = ( 0; 1; 2)0. b. Find the variance-covariance matrix of the previous estimator. c. Compute the estimate s2e of 2. d. Using your answers to parts (b) and (c) nd the variances of ^ 0; ^ 1, and ^ 2. e. Find the tted value ^y1 a nd its variance. f. What is the variance of the rst residual (var(ei))? Exercise 4 Show that the residuals are orthogonal to the matrix X as well as to the tted values ^Y . This is true for simple or multiple regression models. a. e0X = 0. b. e0^Y = 0. c. Use part (a) to show the already known result that Pn i=1 ei = 0.

## University of California, Los Angeles Department of Statistics Statistics 100C Instructor: Nicolas Christou Homework 4 Exercise 1 Consider the following simple regression model yi = 0 + 1xi + i, for which E(i) = 0, E(ij) = 0 for i 6= j, and var(i) = 2. The normal equations discussed earlier in class are: n^ 0 + ^ 1 Xn i=1 xi = Xn i=1 yi ^ 0 Xn i=1 xi + ^ 1 Xn i=1 x2i = Xn i=1 xiyi In matrix form this system of two equations with two unknowns can be expressed as follows:  n Pn i=1 P xi n i=1 xi Pn i=1 x2i  ^ 0 ^ 1  =  Pn i=1 P yi n i=1 xiyi  a. Use matrix algebra to nd the solution for the vector ^ = ( ^ 0; ^ 1)0. b. Use matrix algebra to nd the variance covariance matrix of the vector ^ , i.e.  var( ^ 0) cov( ^ 0; 1) cov( ^ 1; 1) var( ^ 1)  : Exercise 2 Consider the following simple regression model for which i  N(0; ). y1 = 0 + 0:5 1 + 1 y2 = 0 ? 1 + 2 y3 = 0 + 0:5 1 + 3 a. Write the above model in matrix form. b. Find the least squares estimates using vectors and matrices. c. Find the variance-covariance matrix of ^ . d. Find the hat matrix. Verify that the sum of the diagonal elements of the hat matrix is equal to 2 ( Pn i=1 hii = k + 1). e. Generate your own data with n = 3 based on this model and verify that the estimates of 0 and 1 are those given by part (b). Exercise 3 Suppose that you need to t the multiple regression model yi = 0 + 1x1i + 2x2i + i, where E(i) = 0, E(ij) = 0 for i 6= j, and var(i) = 2, to the following data: y x1 x2 -43.6 27 34 3.3 33 30 -12.4 27 33 7.6 24 11 11.4 31 16 5.9 40 30 -4.5 15 17 22.7 26 12 -14.4 22 21 -28.3 23 27 It turns out that (X0X)?1 = 0 @ 1:97015 ?0:05623 ?0:01572 ?0:05623 0:00289 ?0:00091 ?0:01572 ?0:00091 0:00174 1 A and X0Y = 0 @ ?52:3 ?1076:3 ?2220:2 1 A a. Find the least squares estimator of = ( 0; 1; 2)0. b. Find the variance-covariance matrix of the previous estimator. c. Compute the estimate s2e of 2. d. Using your answers to parts (b) and (c) nd the variances of ^ 0; ^ 1, and ^ 2. e. Find the tted value ^y1 a nd its variance. f. What is the variance of the rst residual (var(ei))? Exercise 4 Show that the residuals are orthogonal to the matrix X as well as to the tted values ^Y . This is true for simple or multiple regression models. a. e0X = 0. b. e0^Y = 0. c. Use part (a) to show the already known result that Pn i=1 ei = 0.

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1. Discuss how the establishment of an organizational infrastructure that supports the integration of a career and succession plan competency models and value systems can help employees overcome the doom loop with respect to understanding your own career status.

## 1. Discuss how the establishment of an organizational infrastructure that supports the integration of a career and succession plan competency models and value systems can help employees overcome the doom loop with respect to understanding your own career status.

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The standard normal probability density function is a bell-shaped curve that can be represented as f(z) = 1 p 2    e?z2=2 Use MATLAB to generate a plot of this function from z = ?5 to z = 5. Label the ordinate as frequency and the abscissa as z.

## The standard normal probability density function is a bell-shaped curve that can be represented as f(z) = 1 p 2    e?z2=2 Use MATLAB to generate a plot of this function from z = ?5 to z = 5. Label the ordinate as frequency and the abscissa as z.

10. Which of the following statements is CORRECT? a. The proper goal of the financial manager should be to maximize the firm’s expected cash flows, because this will add the most wealth to each of the individual shareholders (owners) of the firm. b. The financial manager should seek that combination of assets, liabilities, and capital that will generate the largest expected after-tax income over the relevant time horizon. c. The riskiness inherent in a firm’s earnings per share (EPS) depends on the characteristics of the projects the firm selects, which means it depends upon the firm’s assets, but EPS does not depend on the manner in which those assets are financed. d. Large, publicly-owned firms like AT&T and GM, are controlled by their management teams. Ownership is generally widely dispersed, hence managers have great freedom in how they manage the firm. Managers may operate in stockholders’ best interests, but they may also operate in their own personal best interests. As long as managers stay within the law, there are no effective tools that can be used to motivate them to take actions that are in the stockholders’ best interests. e. Potential conflicts of interest can exist between stockholders and managers, and also between stockholders and bondholders.

## 10. Which of the following statements is CORRECT? a. The proper goal of the financial manager should be to maximize the firm’s expected cash flows, because this will add the most wealth to each of the individual shareholders (owners) of the firm. b. The financial manager should seek that combination of assets, liabilities, and capital that will generate the largest expected after-tax income over the relevant time horizon. c. The riskiness inherent in a firm’s earnings per share (EPS) depends on the characteristics of the projects the firm selects, which means it depends upon the firm’s assets, but EPS does not depend on the manner in which those assets are financed. d. Large, publicly-owned firms like AT&T and GM, are controlled by their management teams. Ownership is generally widely dispersed, hence managers have great freedom in how they manage the firm. Managers may operate in stockholders’ best interests, but they may also operate in their own personal best interests. As long as managers stay within the law, there are no effective tools that can be used to motivate them to take actions that are in the stockholders’ best interests. e. Potential conflicts of interest can exist between stockholders and managers, and also between stockholders and bondholders.

Answer: e 10.    Which of the following statements is CORRECT?  … Read More...