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Latest revision as of 17:07, 22 March 2025

Forecasting is a method or a technique for estimating many future aspects of a business or other operation. There are numerous techniques that can be used, including time series methods and regression analysis.

Overview[edit]

Forecasting is an essential part of decision making. Individuals and organizations forecast at all levels of decision making. It may involve taking historical data and projecting it into the future with a mathematical model. Alternatively, forecasting can be about estimating the value of some variable of interest at some specified future date.

Types of Forecasting[edit]

There are two major types of forecasting, which are: qualitative forecasting and quantitative forecasting.

Qualitative Forecasting[edit]

Qualitative forecasting techniques are generally more subjective than their quantitative counterparts. These methods are used when historical data is not available. They are based primarily on the opinion of experts and use less structured methodologies than quantitative ones.

Quantitative Forecasting[edit]

Quantitative forecasting methods are used when historical data on variables of interest is available. They involve the use of statistics, and are based on the assumption that past patterns in data can be used to forecast future data points.

Techniques of Forecasting[edit]

There are several techniques of forecasting which include: Time Series Methods, Causal Models, Regression Analysis, Simulation Models, and Intervention Analysis.

Time Series Methods[edit]

Time series methods are statistical techniques that deal with time series data, or trend analysis. They are widely used where repeated measurements are made over time.

Causal Models[edit]

Causal models are a class of statistical relationships that can be used to forecast the time series under study. The forecast is based on an extrapolation of a mathematical model that fits the historical data.

Regression Analysis[edit]

Regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.

Simulation Models[edit]

Simulation models are mathematical models that use probability distributions to model the processes under study. They are used when the system being modeled is too complex to be accurately described by an analytical model.

Intervention Analysis[edit]

Intervention analysis is a statistical method that helps to assess the impact of an intervention on the time series of interest. It is often used in econometrics, marketing, and process improvement.

Applications of Forecasting[edit]

Forecasting has a wide range of applications and is used in many areas of life and business. Some of the areas where forecasting is used include: Economics, Finance, Supply Chain Management, Marketing, and Human Resources.

See Also[edit]

References[edit]

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