Criminal Justice-COAS | Data Analysis in Criminal Justice I
P595 | 22157 | Verma


This is a course in applied data analysis for graduate students in
criminal justice at Indiana university. The course is an
introduction to probability and statistics and will deal with
various methods of data handling. Topics will include the basic
concepts and measures in statistical analysis; methods for
describing sets of data, measures of central tendency and
dispersion; elementary probability theory and conditional
probability; concepts of statistical inference and decision;
estimation, hypothesis testing and analysis of bivariate
relationships. Special topics discussed will include regression and
correlation, analysis of variance and non-parametric statistics. The
course will incorporate occasional use of set theory and calculus.
The objectives of this course are to acquaint the student with
statistical reasoning and to develop skills in quantitative
techniques that are useful in analyzing criminal justice data.
Format:
There will be lectures, discussion and ‘lab work’ on the computer
that will involve practical handling of crime related data through
the SPSS system software.
Evaluation:
Home Assignments	25%
short quizzes		25%
Mid-Term Exam.		25%
Final Exam.		25%

All quizzes and examinations will be open book format. The final
examination will be based on the analysis of some CJ data using some
of the techniques demonstrated in class.
Recommended Text:
James T. McClave, William Mendenhall, Terry Sincich 2005. Statistics
(latest Edition) Upper Saddle River, New Jersey: Prentice Hall.

Class Meeting:  Tuesday, 8:45-5:15

Instructor:  Professor Arvind Verma, Criminal Justice Department