Required: Albright, Watson & Zappe, "Data Analysis & Decision Making with Microsoft Excel", Duxbury press, 1999. The ISBN number is: 0-534-26124-8, Call number: HD30.215.A37 1999.
For good reference and quick and clean description of statistical concepts you may take a look at the following Schaum's books:
Recommended: M. Spiegel & L. Stephens, "Schuam's outlines Statistics", Third edition, McGraw-Hill 1999. The ISBN number for this book is: 0-07-060281-6
In addition to MBA standing, there are two very strict prerequisites for this course: First: you must have completed a course in introductory statistics roughly covering chapters 2-5 and 7-9. This material will be very quickly reviewed in the first two lectures, but the purpose is solely to refresh your memory. Second: you should be fairly comfortable with Excel (97 or 2000). You don't have to be experts; you won't be required to write VBA macros and such, however you are required to know the basic operations of Excel.
There will be five or six homework assignments and doing them is optional. Students who choose to hand any of the assignments, they will be graded and the score will be counted as 10% of their final grade for each assignment handed in.
There will be two exams, each worth 1/2 of the percentage left over from the assignments (therefore if a student chooses to hand in four of the assignments, they will constitute 40% of her grade, then the two exams will count as 30% of her grade each.
Warning: The exams are going to be very closely related to homeworks, so you are urged to work on all the homeworks, whether you decide to hand them in or not. If you choose not to hand in any assignments it means that each exam will count 50% of your grade. This is extremely risky and will make your exams somewhat of a do or die situation.
Sampling distributions: Random samples from normal populations, distribution of mean and variance, estimation, confidence intervals, hypothesis testing based on samples, type I and II errors, alpha and beta, power of tests, p-values, t distribution and the t-test, two sample tests, multiple sample tests and ANOVA, the F distribution, chi-squared test for normality, non-parametric tests. Reading: Chapters 7, 8 and 9.
Regression inference, assumptions underlying linear regression: linearity, normality, homoscedasticity, independence, distribution of estimated regression parameters, their confidence intervals, testing relevance of explanatory variables, multi-collinearity, deciding what explanatory variables to include, use of ANOVA and F-test to check the fit, prediction using regression. Reading: Chapters 11 and 12.
Topic 3 Week of 3/11: Time series analysis: evolution of data over time, random series, random walks models, regression and time series: trend lines, smoothing techniques: moving averages and exponential smoothers, Holt's method, dealing with seasonality. Reading chapter 13.
Mid-Term Exam Week of 3/11
Spring Break Week of 3/18
Topic 4 Weeks of 3/25, 4/1 & 4/8: Optimization techniques and modeling:
Foundation of optimization models: Linear programming: definition, and examples, duality and interpretation. Sensitivity analysis, the simplex algorithm and 2-and 3-dimensional graphic solution, infeasibility and unboundedness, integer programming, nonlinear programming.
Applications of optimization models: Modeling transportation, network flow and scheduling problems by linear programming, multi-period planning, linear programming in portfolio selection, binary decision making via 0-1 integer programming, covering and packing problems, mixed-integer programming and fixed-cost models, non-linear programming models for portfolio optimization. Reading: Chapters 14 and 15.
Topic 5 Week of 4/22: Simulation modeling: random numbers and random number generators, using random number generators to simulate possible random outcomes, using random number generators to produce various statistical distributions, Applications in projecting future income and revenue and other financial planning, simulating stocks and options prices. Reading: Chapter 16
Final Exam Week of 4/29