Exam 17: Time Series Forecasting and Index Numbers

Given the following data, compute the total error (sum of the error terms).

Consider the following data. Using simple exponential smoothing with α = .2, determine the forecast error for time period 1.

The linear regression trend model was applied to a time series sales data set based on the last 24 months' sales. The following partial computer output was obtained. Write the prediction equation.

The ________ component of a time series reflects the long-run decline or growth in a time series.

Multiplicative decompositions assume that time series components remain essentially constant over time.

Consider the following data and calculate S₂ using simple exponential smoothing and α = .3.

Consider the following data. Calculate S₅ using simple exponential smoothing if S₃ = 19.064 and α = .2.

A sequence of values of some variable or composite of variables taken at successive, uninterrupted time periods is called a

A ________ index is a weighted aggregate price index. It is accurate in its calculation of periodic prices. However, when using this index, it is difficult to compare the prices in different time periods.

Given the following data, compute the total error (sum of the error terms).

Using the price of the following food items, compute the aggregate index numbers for the four types of cheese. Let 1990 be the base year for this market basket of goods.

A ________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

Suppose that the unadjusted seasonal factor for the month of April is 1.10. The sum of the 12 months' unadjusted seasonal factor values is 12.18. The normalized (adjusted) seasonal factor value for April

The ________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales. The following partial computer output was obtained. What is the predicted value of y when t = 17?

All of the following are forecasting methods except

Periodic patterns in time series that repeat themselves within a calendar year or less are referred to as ________.

Simple exponential smoothing is an appropriate method for prediction purposes when there is a significant trend present in a time series.

A ________ index is a weighted aggregate price index that uses the base period quantities as weights in all succeeding time periods.

Three criteria used to compare two forecasting methods are the mean absolute deviation, the mean squared deviation, and the mean absolute percentage error.