Criminal Justice-coas | Data Analysis in Criminal Justice I
P595 | 1474 | Arvind Verma
This is a course in applied data analysis for graduate students in
criminal justice at Indiana University. The course is an
introductrion 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 topisc discussed will include regression and
correlation, alalysis of variance and non-parametric statistics. The
course will incorporate occasional use of set theory and calculus.
The objectiives of this course are to acquaint the student with
statistical reasoning and to develop skills in quantative techniques
that are useful in analyzing criminal justice data.
There will be lectures, discussion and 'lab work' on the computer that
will involve practical handling of crime related data through the SPSS
Home Assignments 20%
Short Quizzes 20%
Mid-term Exam 25%
Project Paper & Final Exam 35% (15%+20%)
All quizzes and examinations will be open book format. the project
paper will involve description of real criminal justice data. The
final examination will be based on the analysis of this data using
some of the techniques demonstrated in class.
"Statistics" by McClave, James T. and Sinich, Terry. 2000. Upper
Saddle River, New Jersy: Prentice Hall
Class Meeting: One 150 minute class per week, 5:45-8:15P, W, LH 023.
Instructor: Professor Arvind Verma, Criminal Justice Department