Data Analysis

This is an introductory course in the most-used methods of basic statistics. The first part of the course is an introduction to descriptive statistics for data, covering topics such as histograms and stemplots, density curves, measures of central tendency, scatterplots, regression, correlation and causality. Other topics covered in the first part include the normal distribution, experimental design and sampling procedures. The second part of the course introduces the statistical inference; topics covered include probabilities, confidence intervals and hypothesis testing. The mathematical foundations of statistical inference will be illustrated with examples from a variety of disciplines such as medicine, business and engineering. There are many statistical packages available and students are free to use any of them (SAS, SPSS, BMDP, Minitab, S-PLUS, Systat, etc.). Excel has many built-in statistical routines even though it is not primarily statistical software. I will often illustrate a statistical procedure using both Excel and SAS. Packaged with the course textbook is a statistical software package called "CrunchIt!", so we may use it as well.
 

The following list indicates the chapters of the textbook covering the above statistical concepts and methods:
• Looking at Data-Distributions (Chapter 1)
• Looking at Data-Relationships ( Chapter 2)
• Producing Data (Chapter 3)
• Probability and Inference (Chapter 4)
• Sampling Distributions (Chapter 5)
• Statistical Inference (Chapters 6, 7, 8)
 

Introduction to the Practice of Statistics (5th Edition) by David Moore and George McCabe (W.H. Freeman, 2006). ISBN 0-7167-6400-8.

Optional (for SAS use): Applied Statistics and the SAS Programming Language (5th Edition) by Ronald Cody and Jeffrey Smith (Prentice Hall, 2006).  ISBN 0-13-146532-5.
 

MAT 130 or placement

The single most important action you can take in mastering the course objectives is to attend class. You are responsible for all material covered, assignments delivered or received, and announcements made in class (regardless weather you attend or not). I reserve the right to use class participation and attendance in resolving borderline grading decisions.

Grading Scale

Email is the primary means of communication between faculty and students enrolled in this course outside of class time. Students should be sure their email listed under "demographic information" at http://campusconnect.depaul.edu/ is correct.

The university and school policy on plagiarism can be summarized as follows: Students in this course, as well as all other courses in which independent research or writing play a vital part in the course requirements, should be aware of the strong sanctions that can be imposed against someone guilty of plagiarism. If proven, a charge of plagiarism could result in an automatic F in the course and possible expulsion. The strongest of sanctions will be imposed on anyone who submits as his/her own work a report, examination paper, computer file, lab report, or other assignment which has been prepared by someone else. If you have any questions or doubts about what plagiarism entails or how to properly acknowledge source materials be sure to consult the instructor.

An incomplete grade is given only for an exceptional reason such as a death in the family, a serious illness, etc. Any such reason must be documented. Any incomplete request must be made at least two weeks before the final, and approved by the Dean of the School of Computer Science, Telecommunications and Information Systems. Any consequences resulting from a poor grade for the course will not be considered as valid reasons for such a request.

School of Computer Science, Telecommunications and Information Systems
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