Podcast
Questions and Answers
______ is a sophisticated weighted moving average method that calculates the average of a time series by giving recent demand values more weight than earlier demand values. The formula for ______ is Ft+1 = Ft + α (Dt - Ft) where t+1 Ft+1 = forecast of the time series for period Dt = actual value of the time series in period t Ft = forecast of the time series for period t α = smoothing constant (0 < α < 1)
______ is a sophisticated weighted moving average method that calculates the average of a time series by giving recent demand values more weight than earlier demand values. The formula for ______ is Ft+1 = Ft + α (Dt - Ft) where t+1 Ft+1 = forecast of the time series for period Dt = actual value of the time series in period t Ft = forecast of the time series for period t α = smoothing constant (0 < α < 1)
Exponential Smoothing
____ is a method in quantitative forecasting that calculates the average of a time series by giving recent demand values more weight than earlier demand values.
____ is a method in quantitative forecasting that calculates the average of a time series by giving recent demand values more weight than earlier demand values.
Exponential Smoothing
The formula Ft+1 = Ft + α (Dt - Ft) is used in ____ method for time series forecasting.
The formula Ft+1 = Ft + α (Dt - Ft) is used in ____ method for time series forecasting.
Exponential Smoothing
In Exponential Smoothing, the smoothing constant α should be such that ____.
In Exponential Smoothing, the smoothing constant α should be such that ____.
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____ is the measurement used to evaluate the accuracy of forecasts.
____ is the measurement used to evaluate the accuracy of forecasts.
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_________ forecasts compiled from estimates of future demand made periodically by members of a company’s sales force
_________ forecasts compiled from estimates of future demand made periodically by members of a company’s sales force
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Executive Opinion – opinions, experiences and technical knowledge of one or more managers are summarized to arrive at a single _________
Executive Opinion – opinions, experiences and technical knowledge of one or more managers are summarized to arrive at a single _________
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Market research – a systematic approach to determine consumer interest in a product or service by creating and testing hypotheses through _________ surveys
Market research – a systematic approach to determine consumer interest in a product or service by creating and testing hypotheses through _________ surveys
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Delphi method – a process of gaining consensus from a group of experts while maintaining their _________
Delphi method – a process of gaining consensus from a group of experts while maintaining their _________
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These qualitative or judgment methods are useful when no historical data are available from which to develop _________ models
These qualitative or judgment methods are useful when no historical data are available from which to develop _________ models
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Causal methods such as linear regression are used when historical data are available and the relationship between the factor to be forecasted and other external or internal factors can be _________
Causal methods such as linear regression are used when historical data are available and the relationship between the factor to be forecasted and other external or internal factors can be _________
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Forecasting is the art and science of predicting future events or future value of a variable of interest. Virtually all management decisions are based on ______.
Forecasting is the art and science of predicting future events or future value of a variable of interest. Virtually all management decisions are based on ______.
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A forecast is a statement of what may be expected to happen, based upon the present conditions and observations interpreted in the light of previous experiences; and is the basis of deciding what action to take in order to secure a desired ______.
A forecast is a statement of what may be expected to happen, based upon the present conditions and observations interpreted in the light of previous experiences; and is the basis of deciding what action to take in order to secure a desired ______.
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Long range, strategic plans by top management are based on forecasts of the type of products consumers will demand in the future and the size and location of product ______.
Long range, strategic plans by top management are based on forecasts of the type of products consumers will demand in the future and the size and location of product ______.
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Planning decisions regarding scheduling, inventory, production, facility, layout and design, workforce, distribution and purchasing among others are functions of customer ______.
Planning decisions regarding scheduling, inventory, production, facility, layout and design, workforce, distribution and purchasing among others are functions of customer ______.
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Accurate forecasting determines how much inventory a company must keep at various points along its ______ chain.
Accurate forecasting determines how much inventory a company must keep at various points along its ______ chain.
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Time series is a pattern formed by repeated observations of demand for a product or service in their order of ______.
Time series is a pattern formed by repeated observations of demand for a product or service in their order of ______.
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In linear regression models, the dependent variable is a function of only one ______
In linear regression models, the dependent variable is a function of only one ______
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The objective of linear regression analysis is to find values of a and b that minimize the sum of the squared deviations of the actual data points from the ______
The objective of linear regression analysis is to find values of a and b that minimize the sum of the squared deviations of the actual data points from the ______
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The theoretical relationship in linear regression models is represented by a straight line equation: y = a + bx where a = y-intercept of the line, and b = ______ of the line
The theoretical relationship in linear regression models is represented by a straight line equation: y = a + bx where a = y-intercept of the line, and b = ______ of the line
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Multiple regression analysis is useful in determining a forecasting equation for the dependent variable as a function of several independent ______
Multiple regression analysis is useful in determining a forecasting equation for the dependent variable as a function of several independent ______
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The dependent variable in linear regression models could be something like ______ (e.g., sales)
The dependent variable in linear regression models could be something like ______ (e.g., sales)
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The simple moving average is useful for forecasting demand that is ______ or does not display pronounced demand behavior
The simple moving average is useful for forecasting demand that is ______ or does not display pronounced demand behavior
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Compute a 3-month and 5-month moving average orders forecast for Serenity Rice Trading Month No.of Cavans of Rice ordered January 120 February 90 March 100 April 103 May 88 June 95 July 78 August 130 September 110 October 105 November - QUANTITATIVE FORECASTING METHODS SOLUTION: (Note that the last column should read “5-Month Moving Average.) QUANTITATIVE FORECASTING METHODS QUANTITATIVE FORECASTING METHODS Time Series Methods Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Determining the precise weights to use for each period of data usually requires some ______-and-error experimentation
Compute a 3-month and 5-month moving average orders forecast for Serenity Rice Trading Month No.of Cavans of Rice ordered January 120 February 90 March 100 April 103 May 88 June 95 July 78 August 130 September 110 October 105 November - QUANTITATIVE FORECASTING METHODS SOLUTION: (Note that the last column should read “5-Month Moving Average.) QUANTITATIVE FORECASTING METHODS QUANTITATIVE FORECASTING METHODS Time Series Methods Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Determining the precise weights to use for each period of data usually requires some ______-and-error experimentation
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Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
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Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 ______
Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 ______
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Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
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Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving average. Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving average. Ft+1 = 0.50 Dt + 0.30 Dt-1 + 0.20 Dt-2 Weighted Moving Average – each historical demand in the average can have its own weight; for example, 0.50 for the most recent period, 0.30 for the second most recent period, and 0.20 for the third most recent period Determining the precise weights to use for each period of data usually requires some trial-and-error experimentation, as well as determining the number of periods to include in the moving ______
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Study Notes
Exponential Smoothing
- Exponential Smoothing is a sophisticated weighted moving average method that calculates the average of a time series by giving recent demand values more weight than earlier demand values.
- Formula: Ft+1 = Ft + α (Dt - Ft), where Ft+1 = forecast of the time series for period t+1, Ft = forecast of the time series for period t, Dt = actual value of the time series in period t, and α = smoothing constant (0 < α < 1).
- The smoothing constant α should be such that 0 < α < 1.
Forecasting Methods
- Executive Opinion: opinions, experiences, and technical knowledge of one or more managers are summarized to arrive at a single forecast.
- Market Research: a systematic approach to determine consumer interest in a product or service by creating and testing hypotheses through surveys.
- Delphi Method: a process of gaining consensus from a group of experts while maintaining their anonymity.
Forecasting
- Forecasting is the art and science of predicting future events or future value of a variable of interest.
- Virtually all management decisions are based on forecasting.
- A forecast is a statement of what may be expected to happen, based upon the present conditions and observations interpreted in the light of previous experiences.
Time Series
- Time series is a pattern formed by repeated observations of demand for a product or service in their order of occurrence.
- The objective of time series analysis is to identify patterns and trends in the data to make informed forecasts.
Linear Regression
- Linear regression is a causal method used when historical data are available and the relationship between the factor to be forecasted and other external or internal factors can be identified.
- Formula: y = a + bx, where a = y-intercept of the line, and b = slope of the line.
- The objective of linear regression analysis is to find values of a and b that minimize the sum of the squared deviations of the actual data points from the line.
Moving Average
- The simple moving average is useful for forecasting demand that is stable or does not display pronounced demand behavior.
- Weighted Moving Average: each historical demand in the average can have its own weight, and the weights are determined through trial-and-error experimentation.
Quantitative Forecasting Methods
- Compute a 3-month and 5-month moving average orders forecast for Serenity Rice Trading.
- The 3-month and 5-month moving average forecasts are used to determine the expected demand for the next period.
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Description
Explore qualitative or judgment methods used in time series forecasting, including Sales Force Estimates, Executive Opinion, Market Research, and the Delphi method. Learn how these approaches help in making future demand predictions.
