Flashcards in BEC 14 - Forecasts and Trends Deck (7):
Identify and describe the two major classes of business forecasting methods.
1. Qualitative: methods that are subjective in nature and based on judgment and opinion.
2. Quantitative: methods that are objective in nature and based on mathematical calculations and determinations.
Identify and describe three classes of qualitative business forecasting methods.
1. Executive opinion: The collective judgment and opinion of executives and managers are used to develop a forecast.
2. Market research: Surveys of customers and others are done to determine preferences and other factors as a basis for formulating a forecast.
3. Delphi method: Uses a consensus developed by a group of experts using a multi-stage process for converging on a forecast.
Identify and describe the two major classes of quantitative business forecasting methods.
1. Time-series models: Use patterns from past data to predict a future value or values. These methods are not concerned with causes of patterns, just the patterns in the data.
2. Causal models: Use assumed relationships between the variable being forecasted and other variables to make projections based on those relationships.
Identify and briefly describe the major types of causal models used for forecasting.
Regression - uses an equation to relate a dependent variable to one or more independent variables to forecast the dependent variable.
Input-output models - describe the flow from one stage, sector, or other component to another in order to forecast values for either the predecessor or successor stage, sector or other component.
Economic models - specify a statistical relationship between various economic quantities to forecast the value of one using the value of another.
Identify the major forms of causal models used for forecasting.
1. Regression models (linear or non-linear);
2. Input-Output models;
3. Economic models.
Identify and briefly describe major time-series patterns.
1. Level - data are relatively constant or stable over time;
2. Seasonal - data reflect up and down swings over short or intermediated periods of time; each swing of about the same timing and level of change;
3. Cycles - data reflect up and down swings over a long period of time;
4. Trend - data reflect a steady and persistent up or down movement over a long period of time;
5. Random - data reflect unpredictable, erratic variations over time.