What is not a characteristic of a random data series?

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Reference no: EM13852384

Question 1. 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

A. 325

B. 225

C. 252

D. 271

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?

A. Alpha and Delta

B. Delta and Gamma

C. Alpha and Gamma

D. Std. Dev and Mean

Question 3. 3. Why is the residual mean value important to a forecaster?

A. Large mean values indicate nonautoregressiveness.

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

C. Large absolute mean values indicate estimate bias.

D. Large mean values indicate the standard error of the model is small.

Question 4. 4. When performing correlation analysis what is the null hypothesis? What measure in Minitab is used to test it and to be 95% confident in the significance of correlation coefficient.

A. Ho: r = .05 p < .5

B. Ho: r = 1 p =.05

C. Ho: r ≠ 0 p≤.05

D. Ho: r = 0 p≤.05

Question 5. 5. In decomposition what does the cycle factor (CF) of .80 represent for a monthly forecast estimate of a Y variable?

A. The estimated value is 80% of the average monthly seasonal estimate.

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

C. The estimated value is .80 of the historical average CMA values.

D. The estimated value has 20% more variation than the average historical Y data values.

Question 6. 6. A Burger King franchise owner notes that the sales per store has fallen below the stated national Burger King outlet average of $1,258,000. He asserts a change has occurred that reduced the fast food eating habits of Americans. What is his hypothesis (H1) and what type of test for significance must be applied?

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

B. H1: u = $1.258,000 A two-tailed t-test.

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

D. H1: p < $1.258,000 A one-tailed test to the right.

Question 7. 7. 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?

A. Time series data of profits by store.

B. Recent 10 year sample of profits by stores.

C. Recent cross section of store profits by city.

D. Trend of a random sample of store profits over time.

Question 8. 8. Sometimes forecasters get lazy or forgetful and do not check the significance of XY data correlations and use the X variable to forecast Y. What is the result of this?

A. Type 2 error

B. Autocorrelation error

C. Type 3 error

D. Type 1 error

Question 9. 9. In exponential smoothing what is the weight of the alpha coefficient for a time series data observation from the 3rd previous period if the original alpha value is set at .3? Is there a formula for this? Where does this come from?

A. The weight cannot be calculated since the data observation is not given.

B. The weight is zero since the alpha value is set relatively high.

C. 0.125

D. 0.103

E. 0.084

Question 10. 10. What is not a characteristic of a random data series?

A. Zero mean with an normal distribution

B. ACF LBQ values greater than a .05 confidence level.

C. Non Autoregressive observations

D. Central tendency

 


Attachment:- Practice Exam 1.DOCX

Reference no: EM13852384

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