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Questions and Answers
What is the key characteristic of qualitative forecasts?
Which forecasting method involves gathering forecasts from top-level executives?
What distinguishes the Delphi Method from other qualitative forecasting methods?
What is the purpose of using associative forecasting techniques?
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What are predictor variables in forecasting?
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What is the purpose of Standard Error of Estimate in regression analysis?
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Which forecasting technique gives more weight to recent data while gradually forgetting older data?
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What does Monitoring Forecast Error involve?
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In regression analysis, what does Simple Linear Regression focus on?
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Why is it important to balance cost and accuracy when choosing a forecasting technique?
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Study Notes
Qualitative Forecasting
- Qualitative forecasts are predictions based on opinions, judgments, and expert insights rather than numerical data.
- Methods include executive opinions, salesforce opinions, consumer surveys, and the Delphi method.
Associative Forecasting Techniques
- Associative forecasting techniques help predict the future by analyzing relationships between variables.
- Predictor variables are factors that might affect what we're trying to predict.
- Regression analysis helps identify patterns between predictor variables and what we're trying to predict.
- Simple Linear Regression analyzes the relationship between two variables.
- Standard Error of Estimate measures the accuracy of predictions.
Monitoring Forecast Error
- Forecast error monitoring involves comparing predictions with actual outcomes to assess accuracy.
- It helps identify the need to adjust forecasting methods if predictions are inaccurate.
Choosing a Forecasting Technique
- Multiple forecasting techniques are available, and the best technique depends on the situation.
- Key factors to consider when selecting a technique are cost and accuracy.
Forecasting Techniques
- Trend Equations: identify patterns of increase, decrease, or stability over time.
- Time-Series Data: data collected over time, showing changes and patterns.
- Moving Average: smooths out data fluctuations by averaging past values to predict future values.
- Exponential Smoothing: gives more weight to recent data, gradually forgetting older data.
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Description
Learn about qualitative forecasting methods which are predictions based on opinions, judgments, and expert insights rather than numerical data. Explore methods like Executive Opinions and Salesforce Opinions.
