The aim of this course is to define and teach the steps of the decision-making process, define the different roles played by qualitative and quantitative approaches to managerial decision making.
Perform cost-revenue-profit analysis, and calculate break-even values,mathematical models for calculating break-even, maximization of profit, and minimization of costs with given business or production constraints,
Time series models(patterns or behaviors of time series data),forecast for time series data, including moving average and exponential smoothing,
Regression models to build linear trend forecast models, calculate forecast accuracy using various measures of error, kinds of problems that linear programming use to solve,
Formulate linear programming models for simple problem and generate a plot of linear inequalities using plotting tools,
Identify the feasible region of a two-variable linear programming problem,
Solve two variable linear programming problems by the graphical solution method using analysis software interpret solutions of linear programming problems for use in business decisions and formulating recommendations,
Di-sensitivity analysis, use the graphical method to describe what happens when coefficients of the objective change,
Recommendations for management action using the results of sensitivity analysis,
Sensitivity analysis, shadow price, reduced cost, sunk cost, and relevant cost,
Interpret answer and sensitivity reports to support business decisions,
Common sources of error in the problem-solving process and suggest strategies for their mitigating,
The concept of utility in decision making and analyze decisions using expected utility approach,
Analyze decision utilities for risk takers and risk avoiders,
Determine how quantitative decision analysis tools can use to support business decisions,
Prepare a formal management report that uses quantitative decision tools to support recommendations and analysis.