MS 393 - Quantitative Management Techniques

• Have awareness that the techniques covered under those topics are available to aid in decision making and forecasting
• Understand when, or to what types of problems the different techniques should be used
• Apply all of the techniques, as appropriate, to solve specific problems

• MA 340  
• MS 340 

• Decision analysis Without Probabilities (maximax, maximin, minimax regret, equal likelihood) With Probabilities (expected value, expected value of perfect information) Sequential decision trees
• Linear Programming Formulation Graphical Solutions Computer solutions Transportation problems
• Facility location techniques Location factor rating Center of Gravity Load distance
• Simulation Techniques
• Waiting line models Single server Multiple server
• Review of Statistics Frequency distributions Normal Binomial Exponential Poisson Descriptive statistics Mean Median Variance Standard deviation Expected value Sampling distributions Sample sizes Central limit theory Tabulated areas o the normal distribution
• Ientifying data patterns Random Stationary Trend Seasonal Cyclical
• Regression Analysis (casual forecasting) Linear regression Multiple regression
• Time series data analysis Moving averages Single exponential smoothing Double exponential smoothing Regression of time series data Winters method