SYLLABUS
202:601 - DATA ANALYSIS IN CRIMINAL JUSTICE
Spring 2009
Wednesday
|
Instructor: |
Jane
A. Siegel, Ph.D. |
|
Office: |
|
|
Phone: |
(856)
225-6143 |
|
E-mail: |
|
|
Website: |
|
|
Office
Hours: |
Wednesday
|
|
Teaching
assistant |
Ines Meier |
REQUIRED TEXT
The
Statistical Imagination, 2nd Ed., Ferris J. Ritchey
The text is available in the bookstore and should
include an SPSS student version disk (v. 14) for use in a Windows environment
(bound with the book). If the data disk is not included, notify the
bookstore immediately.
The book is also available from various on-line
sellers. If you purchase the text from a
vendor other than the bookstore, make sure it contains the CD-ROM with SPSS if
you want to be able to do your homework assignments at home. SPSS is available in the school’s computer
labs so you can use them to complete your SPSS assignments if you don’t
have the version bound inside the book.
COURSE OBJECTIVES
This course
is intended to:
1. Introduce students to
the basic means of measurement and statistical testing used most commonly in
criminal justice and other social sciences and to the steps involved in data
analysis;
2. Equip students with the
skills required to choose appropriate statistical procedures for research,
execute those procedures and correctly interpret the results; and
3. Provide an
understanding of the issues involved in statistical inference and analysis in
order to enable students to examine actual data analysis problems and be
intelligent users of statistical studies.
COURSE DESCRIPTION
This course will provide students with a grounding in the basic tools used in quantitative analysis
in the field of criminal justice and other social sciences along with an
introduction to the statistical issues involved in the design and logic of
research. Students will learn to use
various non-parametric measures of association as well as parametric tests of
significance and will be introduced to the fundamentals of correlation and
regression. Although students will make use of a standard statistical software
package (SPSS), they will also learn the computation of several measures and
statistical tests in order to enhance understanding of the concepts that
underlie them. The course will also provide students with an overview of the
steps involved in the data analysis process and the formulation and testing of
hypotheses.
COURSE REQUIREMENTS
Students are expected to attend class regularly
and to have read assigned material prior to class. Statistics is a subject that
builds upon existing knowledge and absences interrupt that process. Problem
sets will be assigned weekly and are due on the date of the following week's
class, unless otherwise noted. Late
assignments will be accepted only with prior permission of the instructor.
Since
all problem sets will be graded, they are to be done
individually. (Please see the university's academic
integrity policy.) A few ground
rules about problem sets:
1. If you
type any portion of your answers to a problem, you must double-space
!
2. Answers to any problems that require computations should show as
much of the work performed as possible.
Partial credit may be given for answers that are incorrect only because
of an arithmetical error (e.g. a mistake in addition, multiplication
etc.). If no work is shown and the
answer is incorrect, then no credit can be given. You may use calculators and/or a spreadsheet
program like Excel to carry out your calculations.
3. Problems
using SPSS procedures should include printouts of the results where
appropriate.
4. Always
use correct grammar and, where required, complete sentences.
A Sakai
website has been established for the class.
In addition to weekly problem sets, there will be
a mid-term and final exam. Make-up
exams will be given only if, prior to the scheduled exam date, you have obtained
permission to be excused from the exam on that date.
GRADING
Grades will be computed on the following basis:
|
Problem
sets |
50%
(5% each) |
|
Mid-term |
20% |
|
Final |
30% |
A final grade of 70 or above will be required to pass
the course (i.e. obtain a grade of C or above).
ACCOMMODATIONS FOR DISABILITIES
Students with
disabilities requesting accommodations in the class are encouraged to contact
Associate Dean Nathan Levinson, the person charged with evaluating requests for
accommodations due to disability, as soon as possible to better ensure that
such accommodations are implemented in a timely fashion. His office is on the
second floor of the Business and
Assigned readings should be done prior to the date where
they appear. Additional readings may be distributed in class. Students are
responsible for knowing the material in the readings, regardless of whether it
is discussed in class or not. In other words, your problem sets and exams may
include materials from both class lectures and your readings, unless otherwise
noted. Since I may not be able to discuss all of the subjects covered in the
readings, you should take careful notes as you read and ask
me about any topics you do not understand and that I have not reviewed in
class.
Note that the schedule is
subject to change!
|
DATE |
TOPIC |
|
|
1/21 |
Introduction.
Uses of statistics. Levels of measurement. Descriptive statistics. |
Chapters
1-2 |
|
1/28 |
Measures
of central tendency: mode, median and mean. Frequency distributions and the
graphical representation of data distributions. |
Chapters
3-4 |
|
2/4 |
Measures
of dispersion: variance and standard deviation. The normal distribution. |
Chapter
5 |
|
2/11 |
Probability
theory. Uses of the normal probability
distribution. |
Chapter
6 |
|
2/18 |
Understanding sampling distributions. |
Chapter
7 |
|
2/25 |
Estimating
parameters using confidence intervals. |
Chapter
8 |
|
3/4 |
MID-TERM
EXAM |
|
|
3/11 |
Hypothesis
testing. Steps in statistical tests of
significance. |
Chapter
9 |
|
3/25 |
Statistical
inference: using samples to make statements about populations. Single-sample hypothesis testing. |
Chapter
10 |
|
4/1 |
Comparing
means and proportions in two samples: t-tests. |
Chapter
11 |
|
4/8 |
Comparing
means among more than two samples: Analysis of variance. |
Chapter
12 |
|
4/15 |
Testing
for association between nominal-level measures: the chi square
statistic. Single-sample proportions
test using the binomial distribution. |
Chapter
13 |
|
4/22 |
Measuring
association between interval level variables and estimating the effect of one
variable on another: correlation and
bivariate regression. |
Chapter
14 |
|
4/29 |
Multivariate
regression. |
Chapter
15 |
|
Monday 5/11 |
FINAL
EXAM – |
|