Simulation, Applied Statistics

Simulation

When decisions are to be taken under conditions of uncertainty, simulation can be used. Simulation as a quantitative method requires the setting up of a mathematical model which would represent the interrelationships between the variables involved in the actual situation in which a decision is to be taken. Then, a number of trials or experiments are conducted with the model to determine the results that can be expected when the variables assume various values. Simulation can therefore be defined as a procedure whereby one can draw conclusions about the behavior of a given system by examining the behavior of a corresponding model whose cause-effect relationships are similar to those in the actual system. There are a few basic concepts which must be understood before applying the simulating technique.

  1. System: It is that segment to be studied or understood to draw conclusions. In the illustration given above, the market for the product together with the firms' production process constitute the relevant system. Only after the system is defined, can we identify the variables which interact with one another in the system and establish their relationships mathematically.

  2. Decision Variables: A variable, as its name implies, may assume differing values under differing sets of circumstances. Decision variables are those variables whose value is to be determined through the process of simulation. In our illustration, the price to be charged by the firm for its product is the decision variable.

  3. Environmental Variables: These are the variables which describe the environment and are dependent upon that environment in which the system is operating. In the illustration, competitors' average price, consumer preferences and demand, etc. are the environmental variables.

  4. Endogenous Variables: Unlike the environmental variables these are generated within the system itself. In the illustration, quantity sold, sales revenue, total cost and profit are endogenous variables.

  5. Criterion Function: One or more of the endogenous variables or some specified combination of these is used as the criterion function for evaluating the performance of the system. In the illustration, profit is used as the criterion function.

 

Posted Date: 9/15/2012 5:33:55 AM | Location : United States







Related Discussions:- Simulation, Assignment Help, Ask Question on Simulation, Get Answer, Expert's Help, Simulation Discussions

Write discussion on Simulation
Your posts are moderated
Related Questions
The cost of living index number on a some data was 200. From the base period, the percentage enhances in prices were-Rent Rs 60, clothing Rs 250, Fuel and Light Rs 150 and Miscella

In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o

The calculations of arithmetic mean may be simple and foolproof, but the application of the result may not be so foolproof. An arithmetic mean may not merely lack

Multi stage or Cluster Random sampling  Under this method, the random selection is made of primary, intermediate and final units from a given population. The area of investigat

Explanation of standard deviation and variance Describe the importance of standard deviation and variance, what they calculate and why they are required. Importance of char

Construct index numbers of price for the following data by applying: i)      Laspeyre’s method ii)     Paasche’s method iii)    Fisher’s Ideal Index number

just wondering what would be the cost to complete a stats assignment

As one of the oldest multivariate statistical methods of data reduction, Principal Component Analysis (PCA)simplifies a dataset by producing a small number of derived

Uses Arithmetic mean is widely used because of the following reasons: Mean is the simplest average to understand and easy to compute. It

We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that