solution

/in /by

Carry out a situation analysis for the following situations:

a. As a PM, you discover, at month 8 in a ten-month project, that you are 8% over cost. Your Chief Systems Engineer tells you that you can meet budget if the entire project team works a 48-hour week. Your Project Controller estimates only a 50% chance of success with that strategy, but claims that 5% of the work done has been “out of scope.” You have a project status review planned with the customer in two days. What should you do, and in what sequence?

b. As a PM, it is Friday afternoon at 4 P.M. and you receive a call from your customer complaining about the quality of your company’s last report and a bad attitude on the part of your on-site lead engineer. Your customer wants to see you in his office at 9 A.M. next Monday. What should you do and in what sequence?

 
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"

solution

/in /by

The data file birds.csv contains measures on breeding pairs of landbird species collected from 16 islands around Britain over the course of several decades reported in Pimm et al. [1988]. For each species, the data set contains an average time of extinction on those islands where it appeared; the average number of nesting pairs (the average over all islands where the birds appeared, of the nesting pairs per year); the size of the species (categorized as large or small); and migratory status of the species (migrant or resident). It is expected that species with larger numbers of nesting pairs will tend to remain longer before becoming extinct. Pimm et al. were interested in whether, after accounting for number of nesting pairs, size or migratory status has any effect. Furthermore, they were also interested in whether the effect of bird size differs depending on the number of nesting pairs. If any species have unusually small or large extinction times compared to other species with similar values of the predictor variables, it would be useful to point them out. Develop a regression model to predict the time to extinction using the number of nesting pairs and the two categorical variables as predictors; follow the guidelines outlined in section 5.4. Compare your model to the model reported in Pimm et al. [1988].

 
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"

solution

/in /by

For the activity data related to a small project, as shown, draw the PERT chart and find

a. the critical path and its expected time

b. the slack in all other paths

c. the standard deviation associated with the project end date

For the activity data related to a small project, as shown, draw the PERT chart and find a. the...

Design a cost monitoring report that expands the data provided in Table 4.1.

You are at the 18-month point of a 24-month project with a $400,000 budget. The schedule variance has been estimated as $30,000 and the cost variance as $20,000. The BCWS is $300,000.

a. ACWP

b. BCWP

c. ECAC

d. ETAC

Compare these results with those in the EVA example in the text. Why are they different?

In general, for a project:

a. If BCWP > BCWS, is the project early or late? Explain.

b. If ACWP > BCWP, is the project over or under cost? Explain.

c. If ACWP

 
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"

solution

/in /by

The data file co2data.csv contains monthly mean atmospheric CO2 concentrations measured at Mauna Loa, Hawaii, from January 1959 to December 2003. Atmospheric CO2 concentrations show a distinct seasonal pattern, reflecting the annual cycle of plant activities. The data set has four columns: CO2 (monthly CO2 concentrations in ppm), mon (calendar month), year, and months (months since January 1959). The data plot (Figure 6.30) showed an unmistakable increasing temporal trend in CO2 concentrations. In this question you are asked to quantify the magnitude of this increase. A frequently used statistical method for estimating temporal trend is to fit a linear regression model of the CO2 concentration against a time variable (e.g., number of months since a starting point). In this case, the column months in the data set is such a time variable.

(a) Fit a simple regression model using CO2 as the response variable and months as the predictor variable. Quantify the temporal trend (monthly or annual rate of increase in CO2 concentration) and discuss the potential problems of the model. (Hint: plot the residuals against months.)

(b) Refit the model by using mon as a second (factor) predictor and explain the temporal trend in CO2 concentrations.

In both models, the residuals versus fitted plot shows a systematic pattern. What may be the cause of such pattern?

 
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"