Spring 2012

Wednesday 6:00 – 9:30

Instructor: Jane A. Siegel, Ph.D.
Office: 405-07 Cooper Street (entrance at rear)
Room 109
Phone: (856) 225-6143
Office Hours: Wednesday 4:30 – 5:30; Tuesday and Thursday 1:30-2:30
Also by appointment
Teaching assistant Jessica Boatwright(856) 316-8236

Link to Sakai log-in page



The Statistical Imagination, 2nd Ed., Ferris J. Ritchey


The text is available in the bookstore and should include an SPSS student version disk (v. 17) for use in a Windows environment (bound with the book).  If the data disk is not included, notify the bookstore immediately.  The publisher maintains a companion website for the text, which you will be using regularly for datasets and some other materials. It also has some useful study aids.


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.



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.



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.



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.  Sakai is an on-line course management system that provides various resources, including a discussion board that everyone in the class can utilize to pose or answer questions or initiate discussions.  It also has links to the textbook publisher’s website, which contains various resources that you will need for the course, including datasets and computer applications.  The publisher’s website has a list of some sources on the Web for additional statistical support, information, data and even some humor (believe it or not!).  You can download the datasets to your computer by clicking on any name and saving the file to your computer.  You cannot download them to a school computer, but you can put your datasets on a storage device (flash drive, CD) and open them with SPSS in the lab.


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.


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).



Students with disabilities requesting accommodations in the class are encouraged to contact the Disability Services Coordinator for the campus, Tim Pure.  Mr. Pure is charged with coordinating requests for accommodations due to disability, so any student seeking acommodation should contact him as soon as possible to better ensure that the review of your request is completed in a timely fashion.  Mr. Pure can be reached by contacting him at the Rutgers-Camden Learning Center (225-6442); his e-mail address is  Special accommodations will be made upon notification from his office that they are required.  Information about disability services can be found at



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!






Introduction. Uses of statistics. Levels of measurement. Descriptive statistics. Chapters 1-2


Measures of central tendency: mode, median and mean. Frequency distributions and the graphical representation of data distributions. Chapters 3-4


Measures of dispersion: variance and standard deviation.  The normal distribution. Chapter 5


Probability theory.  Uses of the normal probability distribution. Chapter 6


Understanding sampling distributions. Chapter 7


Hypothesis testing.  Steps in statistical tests of significance. Chapter 9




Statistical inference: using samples to make statements about populations.  Single-sample hypothesis testing. Chapter 10


Comparing means and proportions in two samples: t-tests. Chapter 11


Comparing means among more than two samples: Analysis of variance. Chapter 12


Testing for association between nominal-level measures: the chi square statistic.   Single-sample proportions test using the binomial distribution. Chapter 13


Measuring association between interval level variables and estimating the effect of one variable on another:  correlation and bivariate regression. Chapter 14


Bivariate regression (cont’d.) Chapter 15
4/25 Multiple regression. Chapter 15 extension on-line at publisher’s website



FINAL EXAM – 6:00 – 9:00