Qt Primer
Qt Primer
LAUNCH PAD-2011
Pre-Orientation Primer No.11
Quantitative Techniques by Dr. Gaurav Chaudhari
INTRODUCTION
? It is the application of quantitative techniques to the managerial problems. ?
? Quantitative techniques do not make decisions, rather these assists in decision-making process. ?
? While over reliance on the quantitative methods may be harmful so is the failure to make good use of them ?
? Mathematical tools have been used for thousands of years ?
? Quantitative analysis can be applied to a wide variety of problem ?
? Its not enough to just know the mathematics of a technique ?
? One must understand the specific applicability of the technique, its limitations, and its assumptions ?
There are different types of models
? Schematic models ?
? Scale models ?
? Mathematical models ?
Quantitative techniques models are realistic, solvable, and understandable mathematical representations of a situation
? Models generally contain variables (controllable and uncontrollable) and parameters
? Controllable variables are generally the decision variables and are generally unknown
? Parameters are known quantities that are a part of the problem ?
? Mathematical models that do not involve risk are called deterministic models ?
? We know all the values used in the model with complete certainty ?
? Mathematical models that involve risk, chance, or uncertainty are called probabilistic models ?
? Values used in the model are estimates based on probabilities ?
Data may come from a variety of sources such as company reports, company documents, interviews, on-site direct measurement, or statistical sampling.
Input data must be accurate – GIGO rule
The best (optimal) solution to a problem is found by manipulating the model variables until a solution is found that is practical and can be implemented
Common techniques are:
? Solving equations ?
? Trial and error – trying various approaches and picking the best result ?
? Complete enumeration – trying all possible values ?
? Using an algorithm – a series of repeating steps to reach a solution ?
Both input data and the model should be tested for accuracy before analysis and implementation
? New data can be collected to test the model ?
? Results should be logical, consistent, and represent the real situation ?
? Determine the implications of the solution ?
? Implementing results often requires change in an organization ?
? The impact of actions or changes needs to be studied and understood before implementation ?
1. Sensitivity analysis determines how much the results of the analysis will change if the model or input data changes
2. Sensitive models should be very thoroughly tested
Advantages of quantitative techniques
? Provides logical and systematic