BEC 14 - Forecasts and Trends Flashcards Preview

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Flashcards in BEC 14 - Forecasts and Trends Deck (7):
1

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.

2

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.

3

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.

4

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.

5

Identify the major forms of causal models used for forecasting.

1. Regression models (linear or non-linear);
2. Input-Output models;
3. Economic models.

6

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.

7

Identify the major forms of time-series models (mathematical methods) used for forecasting.

1. Naive;
2. Simple mean (average);
3. Simple moving average;
4. Weighted moving average;
5. Exponential smoothing;
6. Trend-adjusted exponential smoothing;
7. Seasonal indexes;
8. Linear trend line.