Exam 20: Time-Series Analytics and Forecasting

To create a seasonally adjusted time series,divide the time series by the seasonal ____________________.

The mean absolute deviation (MAD)and the sum of squares for forecast error (SSE)are the most commonly used measures of forecast accuracy.The model that forecasts the data best will usually have the:

Regression analysis with t = 1 to 80 was used to develop the following forecast equation: = 250 + 7.8t + 1.4Q₁− 1.7Q₂− 1.4Q₃,where Forecast the next four values.

The term "seasonal variation" may refer to:

ebay Storefront Sales The sales figures (in $1000s)have been recorded in an ebay storefront as shown in the following table. ​ ​ -{ebay Storefront Sales Narrative} Describe the cyclical effect (if there is one).

The mean absolute deviation averages the absolute differences between the actual values of the time series at time t and the forecast values at time t + 1.

Which of the following is not true in regard to the weights used in exponential smoothing?

Photo Equipment Store Earnings The quarterly earnings of a chain of Photo Equipment stores have been recorded for the years 2011-2014.These data (in millions of dollars)are shown in the accompanying table. ​ ​ -{Photo Equipment Store Earnings Narrative} Develop a regression model,using indicator variables to represent quarters.

We compute the three-period moving averages for all time periods except the first and the last.

To assess the adequacy of a forecasting model,one measure that is often used is the

In determining monthly seasonal indexes,the first step is to construct a centered moving average with a period of

The actual and forecast values of a time series are shown below. a.Calculate the mean absolute deviation (MAD). b.Calculate the sum of squares for forecast error (SSE)

To calculate the five-period moving average for a time series,we average the value in that time period,the values in the two preceding time periods,and the values in the two following time periods.

After estimating a trend model for annual time-series data,you obtain the following residual plot against time. The problem with your model is that:

In exponentially smoothed time series,the smoothing constant w is chosen on the basis of how much smoothing is required.In general,which of the following statements is true?

A model that can be used to make predictions about long term future values of a time series is

If avoiding large errors is important,____________________ should be used because it penalizes large deviations more heavily than does MAD.

An estimated first-order autoregressive model for stock sales is: .If sales in 2011 were 12,000,the forecast of sales for 2012 is ____________________.

If there is no obvious trend or seasonality in the time series data,and we believe that there is a correlation between consecutive residuals,the autoregressive model may be most effective as a forecasting technique.

A time series can consist of four different components: long-term trend,cyclical variation,seasonal variation,and random variation.