Question

Discuss the differences between the following models and state the advantages and disadvantages of each of these models:

a.                               Forecasting model

b.                              Linear regression model

c.                               Simulation model

Answer 1

Answer a : Forecasting model : Forecasting model is the predictions of the future based on past and present data and helpful to analysis the trends.Example of Forecasting are to judge last period demand.

Advantage of Forecasting method are :

• Performed well in the presernce of low counts.
• Single Forecasting model is easy to build.
• Provides reliable forecast for aggregate level.

Disadvantage of Forecasting method are :

• Loss of information especially individual series dynamic.
• Distribution of forecast to lower level is quite difficult.

b : Linear regression model : linear regression model is a straight regression line which shows the relationship between two or more variables.

Advantage of linear regression model:

• Linear regression model has been of great advantages of learning data analysis.
• Relationship between two variables are study in detail.
• Straight line /linear relationship has been formed.
• Work with any kind of data set available.
• Good and logical information has been attained.

Disadvantage of linear regression model:

• Some assumption that are taken in linear regression are not correct.
• Result provided by the linear regression is not appropriate.

c : Simulation model : simulation model is the study of creating or analysing the digital proto type of a physical model to predict it's performance in the real world. Simulation model is used by the designer or engineers to analyses about the project.

Advantage of simulation model are:

• It is helpful in the prediction of the area in which there is it dangerous to an human being.
• It is usually must cheaper than other models.
• Easier to study the long term effect of the problem.

Disadvantage of simulation model:

• Predictions Only as accurate as the data and rules has been entered.
• Powerful expensive computer hardware needed to do simulation.
• Some natural disaster such as earthquake are difficult to control and estimate.