Course Details

Course Number: 95-796

Statistics for IT Managers

Units: 6

Statistics is the science of summarizing, analyzing, and interpreting data. This class is primarily intended to provide you with the tools to both comprehend statistical analysis and perform it yourself. A strong emphasis will be placed on understanding what the speci c purpose of each statistical tool is.

It is important that you leave the class with the ability to do statistical analysis by hand
and on the computer. In class I will typically take a small data set and show you how to do the
statistical calculations by hand. During the review session you will learn how to perform this
analysis on the computer. To be sure that you have gained mastery of both, you will have both
hand calculations and computer problems on your homework.

This course is divided into three distinct parts:

(I) The first part covers descriptive statistics, which involves calculating and interpreting statistical measures to describe raw data. We will also cover introductory probability theory and key probability distributions. This will be necessary for understanding the latter material.
(II) The second part will focus on the fundamentals of statistical inference, and will provide you with the background for executing and interpreting hypothesis tests and confidence intervals.
(III) The final part of the course covers regression, one of the most widely used and powerful

statistical tools for policy analysis.

Learning Objectives:

The objectives of the course are to provide students with the ability to:
1. Identify and interpret patterns in raw data;
2. Understand basic ideas of probability;
3. Perform and interpret elementary statistical inferences (for example, the capability to compute and interpret hypothesis tests and confidence intervals);
4. Perform and interpret basic regression analyses;
5. Recognize limitations of statistical analysis and identify pitfalls in their interpretation;

6. Use the statistical software package Minitab

Syllabus

Faculty:
Rahul Ladhania
Daniel B. Neill
Janusz Szczypula
Benjamin Zamzow
Jeremy Weiss