1. You are given only three quarterly seasonal indices and quarterly seasonally

Question

1.

You are given only three quarterly seasonal indices and quarterly seasonally adjusted data for the entire year. What is the raw data value for Q4? Raw data is not adjusted for seasonality.

Quarter   Seasonal Index             Seasonally Adjusted Data

Q1              .80                               295

Q2              .85                               299

Q3             1.15                              270

Q4              ---                                271

(Points : 3)        325
       225
       252
       271

Alpha and Delta

Delta and Gamma

Alpha and Gamma

Std Dev and Mean

Ho: r = .05    p < .5

Ho: r = 1     p =.05

Ho: r ? 0      p?.05

Ho: r = 0       p?.05

The CEO of Home Depot wants to see if city size has any relationship to the current profit margins of the company stores. What data type will he likely use to determine this?

Simple with a very low trend coefficient.

-24

-348

-892

-62

-378

-489

-342

34

490

23

578

Given the data series below for variables Y (Monthly Inventory Balance) and X (Monthly Sales) are they significantly correlated at the 95% confidence level and how can you tell? (This data also appears in the docsharing download for Exam 1 excel worksheet under the problem 20 tab.)

Ending Inv. Bal. Y

Monthly Sales X

1544

5053

1913

5052

2028

7507

1178

2887

1554

3880

1910

4454

1208

3855

2467

8824

2101

5716

Are the decomposition fit period residuals random? Why or why not?

       Both models produced positive and negative forecast residuals that appear to be random.

       Both models tend to over-forecast the hold out period and produce non random forecast residuals.

       Both models tend to under-forecast the hold out period and produce forecast residuals that are not random.

       The decomposition model produced greater accuracy early in the forecast period while the exponential smoothing model produced better accuracy later in the forecast period.

Question 2.2. One model of exponential smoothing will provide almost the same forecast as a liner trend method. What are linear trend intercept and slope counterparts for exponential smoothing?(Points : 3)       

Alpha and Delta

      

Delta and Gamma

      

Alpha and Gamma

      

Std Dev and Mean

Explanation / Answer

1.1

1.17

2.2

Alpha and Gamma

3.3

Small mean values indicate the total amount of error is small.

4.4

Ho: r ? 0      p?.05

5.5

the estimate is .80 of the forecasted Y trend value.

6.6

H1: u < $1.258,000 A one-tailed t-test to the left.

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