*We are the Amazon Partner and students can purchase the books shown on this page. We are also providing an authentic solution manual, formulated by our SMEs, for the same.This book provides coverage over the full range of analytics--descriptive, predictive, prescriptive--not covered by any other single book. It includes step-by-step instructions to help students learn how to use Excel and powerful but easy to use Excel add-ons such as XL Miner for data mining and Analytic Solver Platform for optimization and simulation. Sample questions asked in the 1st edition of essentials of business analytics: Air pollution control specialists in southern California monitor the amount of ozone, carbon dioxide, and nitrogen dioxide in the air on an hourly basis. The hourly time series data exhibit seasonality, with the levels of pollutants showing patterns that vary over the hours in the day. On July 15, 16, and 17, the following levels of nitrogen dioxide were observed for the 12 hours from 6:00 a.m. to 6:00 p.m.: a. Construct a time series plot. What type of pattern exists in the data? b Use a multiple linear regression model with dummy variables a s follows to develop an equation to account for seasonal effects in the data: Hour1 5 1 if the reading was made between 6:00 a.m. and 7:00a.m.. 0 otherwise. Hour2 5 1 if the reading was made between 7:00 a.m. and 8:00 a.m.. 0 otherwise. . . . Hour11 5 1 if the reading was made between 4:00 p.m. and 5:00 p.m., 0 otherwise. Note that when the values of the 11 dummy variables are equal to 0, the observation corresponds to the 5:00 p.m. to 6:00 p.m. hour. c. Using the equation developed in part b, compute estimates of the levels of nitrogen dioxide for July 18. d. Let t 5 1 to refer to the observation in hour 1 on July 15. t 5 2 to refer to the observation in hour 2 of July 15. ? and t 5 36 to refer to the observation in hour 12 of July 17. Using the dummy variables defined in part b and t s , develop an equation to account for seasonal effects and any linear trend in the time series. e. Based upon the seasonal effects in the data and linear trend estimated in part d, compute estimates of the levels of nitrogen dioxide for July 18. f. Is the model you developed in part b or the model you developed in part d more effective? Justify your answer. The Ajax Company uses a portfolio approach to manage their research and development (R&D) projects. Ajax wants to keep a mix of projects to balance the expected return and risk profiles of their R&D activities. Consider the situation where Ajax has six R&D projects as characterized in the table. Each project is given an expected rate of return and a risk assessment, which is a value between 1 and 10 where 1 is the least risky and 10 is the most risky. Ajax would like to visualize their current R&D projects to keep track of the overall risk and return of their R&D portfolio. a. Create a bubble chart where the expected rate of return is along the horizontal axis, the risk estimate is on the vertical axis, and the size of the bubbles represents the amount of capital invested. Format this chart for best presentation by adding axes labels and labeling each bubble with the project number. b. The efficient frontier of R&D projects represents the set of projects that have the highest expected rate of return for a given level of risk. In other words, any project that has a smaller expected rate of return for an equivalent, or higher, risk estimate cannot be on the efficient frontier. From the bubble chart in part a., what projects appear to be located on the efficient frontier? Resorts&Spas, a magazine devoted to upscale vacations and accommodations, published its Reader?s Choice List of the top 20 independent beachfront boutique hotels in the world. The data shown are the scores received by these hotels based on the results from Resorts&Spas? annual Readers? Choice Survey. Each score represents the percentage of respondents who rated a hotel as excellent or very good on one of three criteria (comfort, amenities, and in-house dining). An overall score was also reported and used to rank the hotels. The highest ranked hotel, the Muri Beach Odyssey, has an overall score of 94.3, the highest component of which is 97.7 for in-house dining. a. Determine the estimated multiple linear regression equation that can be used to predict the overall score given the scores for comfort, amenities, and in-house dining. b. Use the F test to determine the overall significance of the regression relationship. What is the conclusion at the 0.01 level of significance? c. Use the t test to determine the significance of each independent variable. What is the conclusion for each test at the 0.01 level of significance? d. Remove all independent variables that are not significant at the 0.01 level of significance from the estimated regression equation. What is your recommended estimated regression equation? To save on expenses, Rona and Jerry agreed to form a carpool for traveling to and from work. Rona prefers to use the somewhat longer but more consistent Queen City Avenue. Although Jerry prefers the quicker expressway, he agreed with Rona that they should take Queen City Avenue if the expressway has a traffic jam. The following payoff table provides the one-way time estimate in minutes for traveling to or from work: Based on their experience with traffic problems, Rona and Jerry agreed on a 0.15 probability that the expressway would be jammed. In addition, they agreed that weather seemed to affect the traffic conditions on the expressway. Let The following conditional probabilities apply: a. Use Bayes? theorem for probability revision to compute the probability of each weather condition and the conditional probability of the expressway being open, s 1, or jammed, s 2, given each weather condition. b. Show the decision tree for this problem. c. What is the optimal decision strategy, and what is the expected travel time?
Get immediate access to 24/7 Homework Help, step-by-step solutions, instant homework answer to over 40 million Textbook solution and Q/A
Pay $7.00/month for Better Grades