P595 | 1454 | Arvind Verma

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