ITIS 1P97 Lecture Notes - Exponential Smoothing, Confidence Interval, Sampling Distribution

• School: Brock University
• Department: Information Technology Information Systems
• Course: ITIS 1P97
• Professor: Dipanjan Chatterjee

Document Summary

Quantitative business modeling: opportunity/ problem recognition (most important step) Should carefully investigate the situation of concern: model formulation (most time consuming steps according to experts) Transforming the complex opportunity or problem into a mathematical formula. The simpler the model, easier the manipulations and the solution but the less representative it will be of the real life problem. Most important is determining the components and key variables of the model when influence diagram is drawn. 3 basic components: independent, dependent, and uncontrolled variables: data collection, analysis of the model. Representative of system"s behavior under real world situation: implementation and project management. Communicating the results of the study and the modeler"s recommendation. Actually applying managerially approved action through the project management. Approaches to data collection: groups or cross-sectional and time series. Types of observations: categorical, nominal, ordinal, numerical, discrete, continuous. Excel can calculate both variance of population and variance of sample.