Course Description
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					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.
Required Text:
McClave, James T. and Sincich, Terry. 2000. Statistics. (8th Edition).
Upper Saddle River, New Jersey: Prentice Hall.
Schedule of Chapter Readings and Exams.

Week				Topic Coverage				
	
1	01/11	Data Analysis: Introduction to SPSS & Graphical/
Numerical Measures
				ch 1-2 p 1-55
2	01/18	Set Theory; Data Description Methods
				ch 2 p 56-98
3	01/25	Probability
				ch 3 p 99-162				
	
4	02/01	Calculus & Discrete Random Variables- The Binomial
Distribution
				ch 4 p 163-208				
	Quiz 1*
5	02/08	Continuous Random Variables- The Normal Distribution
				ch 5- 209-252				
		
6	02/15	Sampling and Sampling Distributions
				ch 6- 253-278	
7	02/22	Estimation of Population Parameters: Confidence
Intervals
				ch 7- 279-320				
	Quiz 2
8	02/29	General Concepts of Hypothesis Testing & applications
				ch 8- 321-372		
9	03/07	MID-TERM EXAM
						
10	03/21	Comparing two population means
				ch 9 p 373-434
11	03/28	Comparing More than Two Means: Analysis of Variance
				ch 10 p 435-504
12	04/04	Simple Linear Regression & Correlation
				ch 11- 505-576				
	Quiz 3
13	04/11	Multiple Regression and Model building
				ch 12- 577-712				
14	04/18	Contingency Tables			
				ch 713-744				
		
15	04/25	Non-Parametric Statistics
				ch 745-794				
	Quiz 4*
16	05/05	Final Examination Paper due
									
			
Note: Bring a pre-formatted PC compatible blank diskette to every
class
* in-class quiz

Class Meeting:  Monday, 2:30 - 5:00 p.m., BH 108

Instructor:  Professor Arvind Verma, criminal justice department