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QDM Exam #2

Ch. 8

Quantitative Forecasting Methods Forecast is based on mathematical modeling.
Executive Opinion Forecasting method in which a group of managers collectively develop a forecast.
Market Research Approach to forecasting that relies on surveys and interviews to determine customer preferences.
Delphi Method Approach to forecasting in which a forecast is the product of a consensus among a group of experts.
Time Series Models Based on the assumption that a forecast can be generated from the information contained in a time series of data.
Time Series A series of observations taken over time.
Causal Models Based on the assumption that the variable being forecast is related to other variables in the environment.
Level or Horizontal Pattern Pattern in which data values fluctuate around a constant mean.
Trend Pattern in which data exhibit increasing or decreasing values over time.
Seasonality Any pattern that regularly repeats itself and is constant in length.
Cycles Data patterns created by economic fluctuations.
Random Variation Unexplained variation that cannot be predicted.
Naive Method Forecasting method that assumes next period's forecast is equal to the current period's actual value.
Simple Mean or Average The average of a set of data.
Simple Moving Average A forecasting method in which only n of the most recent observations are averaged.
Weighted Moving Average A forecasting method in which n of the most recent observations are averaged and past observations may be weighted differently.
Exponential Smoothing Model Uses a sophisticated weight average procedure to generate a forecast.
Trend-Adjusted Exponential Smoothing Exponential smoothing model that is suited to data that exhibit a trend.
Seasonal Index Percentage amount by which data for each season are above or below the mean.
Linear Regression Procedure that models a straight-line relationship between two variables.
Correlation Coefficient Statistic that measures the direction and strength of the linear relationship between two variables.
Forecast Error Difference between forecast and actual value for a given period.
Mean Absolute Deviation (MAD) Measure of forecast error that computes error as the average of the sum of the absolute errors.
Mean Squared Error (MSE) Measure of forecast error that computes error as the average of the squared error.
Forecast Bias A persistent tendency for a forecast to be over or under the actual value of the data.
Tracking Signal Tool used to monitor the quality of a forecast.
Created by: bradbrown1122