Department of Sociology, Anthropology, and Criminal Justice

Valdosta State University

Valdosta, Georgia 31698-0060

(229) 333-5943

CRJU 3401A: Criminal Justice Data Analysis

 

Instructor: Dr. Wilson Huang                                         Credit hours: 3

Phone: (229) 333-5486                                                   Semester/Year: Summer IV, 2004

Office: University Center 1142                                       Classroom: University Center 1148

E-mail: whuang@valdosta.edu                                        Class day/time: M-F/1:00-3:35pm

                                                                                                                    3:35-4:00pm (review)

Office Hours:    11:30am- 1:00pm, Tuesday and Thursday

I will be available to help you in my office during the above posted hours. If your schedule conflicts with my office hours, we can set up a special time to discuss your needs. Also, if you prefer to have an uninterrupted discussion with me, I recommend that you schedule an appointment with me.

 

Prerequisites

CRJU 1000 – Introduction to Criminal Justice

 

Course Description

The primary purposes of the course are to provide students with a statistical background in data analysis, and to have students develop computer skills important to the evaluation and management of empirical data.  During the course, students will learn how to access and use different computer programs and other resources in the lab.  The course will focus on applied statistics and inferential logic used in criminal justice and other criminological research.  Major topics include measures of central tendency, test of statistical significance, bivariate association, comparison of means, correlation, and regression analyses.  Computer exercises are used to familiarize students with important features of statistical software.  Students will need to employ the computer package MicroCase, a program that combines statistics with real data, to complete their exercises.  Students will learn how to use MicroCase to manage, analyze, and interpret data.  It is anticipated that the instruction of applied statistics in conjunction with the usage of MicroCase will provide students with practical skills in both statistics and computer.

 

Course Objectives

1. To prepare students to conduct various data analyses using knowledge and tools derived from statistics.

2. To familiarize students with descriptive and inferential statistics to be used in social science research.

3. To make students a criminal justice data analyst who can apply statistics and computer skill in interpretation and presentation of data.

4. To enhance students’ understanding of statistics through hand computation, lab exercise, and real data.

 

Required Texts

William Fox (2003). Social Statistics (4th edition). Belmont, CA: Wadsworth/Thomson Learning.

 

William Fox (2003). A MicroCase Workbook for Social Statistics (4th edition). Belmont, CA: Wadsworth/Thomson Learning.

 

Other Materials Required for Class

A hand-held calculator with addition/subtraction/multiplication/division and square-root functions

A 3 ˝ inch, double-sides, high-density, IBM-formatted computer disk

 

 

 

Class Format

The class will consist of regular lectures and computer exercises.  The lectures will cover issues on formulas, computation, and application of statistics, while labs will emphasize on statistical analyses of actual data using MicroCase.

 

Course Requirements

1). Examinations: There will be two non-cumulative exams, and a final comprehensive examination.  The final exam will be given in an open book format.  Each test will be taken in the lab and will cover the assigned readings, handouts, lectures, and exercises.  Multiple choice questions and computational questions will be used for each exam.

2). Computational assignments and computer exercises: Three computational assignments will be given to students and are due on the dates specified on the assignment sheets. Computer exercises are provided on the MicroCase workbook, and will be performed periodically in the lab.  Any assignment and exercise submitted after the due date will be marked down at least 50% of the designated points.  The student who submitted a late assignment also needs to provide the instructor a written explanation.

 

3). Reading assignments: The reading assignments will correspond generally to what is going on in class, but in many cases the materials presented in class will be organized in a form different from what you read from the text.  Students should consider all the materials discussed in the text and class to be required.

 

4). Attendance and participation: Each student is expected to attend all classes.  A student should not miss more than two classes.  When a student misses more than 20% of the scheduled classes, he/she will be subject to receiving a failing grade.  If students miss a class for any reason, students will be held responsible for all materials covered and announcements made in your absence.  Participation in classroom discussion is strongly encouraged.  Students should make comments and ask questions that will benefit the entire class.  Students will be graded on both their attendance and the amount and quality of their contribution to classroom discussion.

Grading System

Course grade will be based upon examinations, computational assignments, computer exercises, and class participation. The specific percentages of each of the elements are described below.

            Three exams (100 points each):                                      60%     (your average score x .60)

            Three computational assignments (6 points each):            18%    

            MicroCase exercises (1 to 2 points each):                       16%    

            Attendance and participation (4 points total):                     6%

            ------------------                                                              ----

            Total                                                                             100%

 

Grade distribution: A= 90-100; B= 80-89; C= 70-79; D= 60-69; F= below 60

 

The following example illustrates how your grade is calculated.  Let’s assume the average score of your tests is 90.  This average score weighted by 60% equals 54 (i.e., 90*.60=54).  Then you sum this weighted test score with the other three performance scores.  Assuming that you got 16 points for computational assignments, 15 points for MicroCase exercises, and 5 points for participation, the sum of these scores plus the exam score would be 90 points (i.e., 54+16+15+5), which equalizes you for an “A” grade.

 

Grades for any exams, assignments, or the course will not be posted on-line or given by e-mail or telephone. If you’d like to know your grades prior to receiving official notice from the registrar, you may leave a self-addressed, stamped envelope with the instructor.

 

Make-up Exam

The instructor is not under any obligation to give a make-up exam unless the student has a valid excuse.  Valid excuses are those recognized by the University and include illness, religious observation, participation in University activities at the request of the University, or compelling circumstances beyond the student’s control.  The student is required to contact the instructor prior to the scheduled exam.  Failure to give prior notice of absence for a scheduled exam will result in the student receiving a zero for that exam.  If the student misses an exam, it is the student’s responsibility to schedule a make-up.  The student must take the make-up exam within a week following the scheduled exam date.

 

Rules on Disruptive Conduct

Students should refrain from participating in disruptive or disrespectful behavior in the classroom, including mindless talking, arriving late/leaving early, drinking or eating food, or passing unrelated notes. The instructor reserves the right to ask a student leave if the student engages in disruptive behavior.

 

Policy on Academic Student Conduct Code

Exams and assignments are to be completed by the student only.  Cheating on the exam or receiving unjustified help with assignments is punishable by expulsion and other disciplinary measures. For complete details on Valdosta State University’s policy on academic honesty, please refer to the section of Student Code of Ethics of the Student Handbook on-line or in hardcopy.

 


Class Schedule

Dates                           Topics

 

7/6-7/9                          Review Syllabus, Statistics and Variables (Chap. 1)

Frequency and Percentage Distributions (Chap. 2)

                                    Averages (Chap. 3)

                                    Measures of Variation (Chap. 4)

 

7/12 (Monday)              Exam 1

 

7/13-7/16                      Cross-tabulation (Chap. 5)

The Chi-Square Test of Statistical Significance (Chap. 6)

                                    Measures of Association for Cross-tabulations (Chap. 7)

 

7/19 (Monday)              Exam 2           

 

7/20-7/23                      Comparison of Means and t Test (Chap. 8)

Analysis of Variance (Chap. 9)

            Regression and Correlation (Chap. 10)

                        Multivariate Cross-tabulation (Chap. 11)

            Multiple Regression and Correlation (Chap. 12)

 

7/23 (Friday)                Final Exam

 

Note: The course syllabus provides a general plan; it is to be expected that we will deviate somewhat from this schedule as we spend more time on some topics and less time on others.