Problem 1:

The Dow Jones Industrial Average (DJIA) is a widely followed stock market indicator. The values of the DJIA from 1971 to 2000 were used in the analysis below.

1. Examine the results presented here. Explain what type of trend model is being fit to the DJIA and report the results of the ordinary least squares fit of the model.
2. Is there evidence of autocorrelation present in these results? Summarize this evidence and be sure to test an appropriate hypothesis for autocorrelation of errors. If first order autocorrelation of errors is present, what are the consequences for this regression model?
3. Describe a correction procedure for the above problem if the first-order autocorrelation coefficient is known to be 0.750.

Problem 2:

Printouts are supplied below for four estimated trend models. The dependent variable is hospital patient admissions (PAT). Other variables include LPAT = natural log of PAT, PATLl = PAT with a one period lag, YEAR = last two digits of the year, and \(\mathrm{YSQ}=\mathrm{YEAR}\) squared. The frequency of the data is annual over a twenty-year period.

1. Describe each trend model and report the estimated model.
2. Consider each model for use as a potential forecasting model.

1. Each model has been used to forecast one period ahead (observation 21 on your printouts). Report these forecast values, the standard errors of the forecasts, and $95 \%$ confidence limits on these forecasts.
2. Which model would you recommend as an appropriate trend model and why? Please be specific.

Case 1:

Nine similar machines are used in a manufacturing process at an assembly plant. The operations manager would like to develop a model to determine the factors that affect repair costs of the machines. He suspects that the repair costs for the machines may be influenced by the operator of the machine. He has asked you, his recently hired Business Analyst, to perform the analysis and report back to him. The SAS file on the next page reports the programming and the data you used to analyze the problem at hand. The variables used are repair costs (COST) for the machines over the past six months, the age (AGE) of each machine in years at the beginning of the six month period, the number of items processed (ITEMS) by the machine during the period, and the operator of the machine (OPER). The results of the SAS run also follow.

Summarize your findings for the plant manager.

Case 2:

The Employee Benefit Research Institute (EBRI) issued a news release "Saving in America: Three Key Sets of Figures," on October 25,2005 . In 2005 , about \(69 \%\) of workers said they and /or their spouses have saved for retirement. The following analysis sampled 100 workers from each age group who have stated that they have not saved for retirement in order to determine if there is a relationship between age and income bracket for non-savers.

The age brackets are as indicated.

The five levels of income are: A, less than $25,000

\(\begin{aligned}

&\text { B, } \\) 25,000 \text { to } \$ 49,999 \\

&\text { C, } \$ 50,000 \text { to } \$ 99,999 \\

&\text { D, } \$ 100,000 \text { to } \$ 249,999 \\

&\text { E, } \$ 250,000 \text { and up. }

\end{aligned}$

Summarize these findings.

Price: $16.93

Solution: The downloadable solution consists of 7 pages, 993 words and 5 charts.
Deliverable: Word Document