Consider the activities, durations, and predecessor relationships in the following network, shown in Table 6 below. Draw the network and answer the questions that follow. Table 5 Activity Description Predecessor(s) A B C Optimistic Most Likely Pessimistic (Weeks) 10 Immediate (Weeks) (Weeks) 4 7 2 8 A 8 20 A 12 16 D B 1 2 3 D, C C 6 2 8. 22 F F 2 2 10 E, G, H 4 1 12 3 a) What is the expected time for activity B? b) What is the variance for activity B? c) Based on the calculation of estimated times, what is the critical path? d) What is the estimated time of the critical path?

The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?

The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?

Using Table 5.3, choose the appropriate survey method(s) you would use to collect primary data for one of your information needs. What sampling method would you use?

Give an example of a nonprogrammed decision.

Cousins Jeri Lynn De Bose, Tish Hoover, and Josephine (Joey) Parks looked forward to meeting up during the Christmas holidays to compare notes on the results of midyear teacher evaluations. All were public school teachers in districts scattered over the state. In the pressured search for new levels of teacher accountability demanded by legislators, the state department of education joined 16 other States in implementing a new teacher evaluation system. The goal is to hold teachers account-able for student learning progress in the classroom. Under the guidance of the National Council for Teacher Quality, criteria varies by State, but in most cases, 40 percent of each teacher's accountability score would be based on the principal's evaluation and ranking based on personal observation, 30 percent would be based on personal observation by a master teacher from outside the district, and the Other 30 percent would be based on student test score gains. The state department of education would set a performance goal each school district, and the principal would set a performance goal for each teacher. In preparation, the State conducted intensive training sessions for principals and designated master teachers who would conduct the evaluations based on four class observations per teacher Officials used standardized achievement tests to derive value-added scores that measure student learning over the year. Teacher ratings were 1-5, with I am being the lowest and 5 representing near perfection. The publication of the first year's evaluations stirred interest and controversy, particularly among teachers who worried about the possible long-term effects on job retention and tenure. Now, with the first-year evaluations in hand, the three cousins pored over their experiences. The three represented different types of school systems within the state. Jeri Lynn worked for a metropolitan system in the state capital. The system included many low-income students whose first language was nor English, and several schools within the system were teetering on the brink of State takeover if improvement in student scores didn't materialize this school year. Tish worked in a county System dominated by upper-income residents, and Joey taught in the rural community in which all three grew up. The rural community had high unemployment, and a low percentage of graduates went on to college. As a result, the cousins came to the table with differing teaching experiences. "The numbers are all over the place," Jeri Lynn remarked as she studied the pages. "The whole system is flawed, and they need to make changes," Joey said. "It's too subjective. The principal and master teacher observations are subjective because there are personal factors that affect a true outcome." "Yeah, look at the numbers from your upper-income district," Jeri Lynn said to Tish. "How can 60 percent of the teachers score 5s?' Tish chuckled. "Yeah, lucky us. Our schools are overflowing with children from wealthy families. These are the kids who will apply to Ivy League schools. I can tell you that the principals are going to avoid confrontation on all fronts. No principal is going to give any indication that their students are receiving an education that's less than perfect, and that means cramming the rankings with 5s. They claim a higher level of motivation for students, and thus the selection of an elite team of educators. So with those pressures, I don't think we get personal feedback that is accurate." "At the other end of the spectrum, we have my rural district," Joey said. "The big problem is that the principals know everyone and have longstanding relationships with everyone in the county, so I think scores are based on personal history. We could almost predict who would get high or low scores before the observations. For principals, it can go back as far as 'his daddy and my daddy hated each other in high school, and now I get to evaluate his daughter "I think that in many cases, principals feel pressure to align scores with state expectations. The stare expected my district to have high scores and expected rural schools such as yours to be lower," Tish said. "But isn't that partially offset by lower goals for the rural school distracts responded Joey. "The key to the accountability system is the principal in each school," Jeri Lynn suggested. "With several of the schools in Metro teetering on the edge of state takeover by the end of the year, we had lots of strict principals who wanted to hold our feet to the fire with lower scores." "I thought the whole idea was to provide the teachers With feedback so that we would know the areas where we need improvement," Tish said. "The principals were supposed to conduct two observations in the fall and two more in the spring," Jeri Lynn said. think that's asking too much of them when they already have so much on their plates. I think a lot of them are skimping on their visits. know I only had one observation last semester, and I'm sure Mr. Talley just faked the second set of numbers. The master teachers make only two observations a year, which may be more objective but counts for less." "I'm wondering, too, how a principal measure performance in a course area outside his area of expertise, such as math," Joey said. "If the guy has a phobia about math, anything the teacher says or does is going to 100k brilliant-thus a 5." Tish and Jeri Lynn looked at each other and laughed. "Maybe we picked the wrong subjects," Tish said. "My question is one of perception," Jeri Lynn said. "A large percentage of my students are ELL. That affects their scores. How do you measure a 3 in my situation against a 5 for Tish? At the end of the school year, little Carlos is thrilled that his reading in English has improved, but there`s no Big Bang here. a slow steady improvement that may not actually show up in big strides for a couple of years: "So, the question is how do they create a system that is fair?" Tish asked. "And accurate," added Jeri Lynn. How might the state control the accuracy of principals who are conducting teacher evaluations? Explain.

The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?

The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?

The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?

Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.