# syllabus

## syllabus

• Submitted By: Yun-Hu
• Date Submitted: 10/13/2015 6:30 PM
• Words: 1337
• Page: 6

﻿OPRE 433: Probability, Statistics, and Forecasting
Fall 2015, Monday and Wednesday 10:30-11:45am, Location: PBL 202

Dr. Alireza Kabirian
Instructor Office Hours:
Tuesday: 4:30-5:30pm
Thursday: 2:30-3:30pm
Or by appointment (I am pretty accessaible)
E-mail: axk821@case.edu

Office Phone: (216)-368-2506

Office: PBL 324

Teaching Assistant: Yiheng Hu TA’s office hours: ??? at Tuesday 1pm - 3:30pm

Course Overview: Companies, government agencies, and nonprofit organizations can collect prodigious amounts of data with relative ease, but the data become information only after they are organized, analyzed, and communicated. Data analysis to create quantitative information is a prerequisite to effective management. In this course you should learn useful tools from probability and statistics to analyze data.
Before you analyze data, you should look at the data and describe them. So this course begins with descriptions of data using the software JMP. After presenting the probability theory foundation on which statistics rests, the course introduces the important concepts of random variables and their probability distributions. It elicits the properties of several particularly important distributions, including the binomial, Poisson, and normal.
The course then turns to statistical analysis. It discusses the central limit theorem, which explains why data often appear to be normally distributed, and the Palm-Khintchine theorem which explains why data often appear to have a Poisson distribution.
The next module introduces methods for estimating parameters and testing hypotheses when the data sample is large. After that, we develop parallel methods when the data sample is small. Then the course turns to regression, namely, the linear dependence of a variable on other variables. We emphasize the detection and avoidance of some of the deadly sins of regression, and the surprising flexibility of regression models....