CCJS 200: STATISTICS FOR CRIMINAL JUSTICE & CRIMINOLOGY
SPRING 2014
“Statistical thinking will one day be as important for good citizenship as the ability to read and write.”
~H.G. Wells~
PROFESSOR
Brian D. Johnson, Ph.D.
2220K LeFrak Hall
Phone: (301) 405-4709
Email: bjohnson@crim.umd.edu
OFFICE HOURS
Tuesday
Thursday
By appointment
1:45pm – 3:00pm
1:45pm – 3:00pm
MEETING TIMES
Lecture:
Tuesday & Thursday 12:30pm – 1:45pm (Marie Mount Hall, 1400)
Discussion Sections:
Section 0101:
Section 0102:
Section 0103:
Section 0104:
Section 0105:
Section 0106:
Thursday 3:00pm–3:50pm
(KEY 0121)
Thursday 2:00pm–2:50pm
(WDS 1130)
Friday
12:00pm–12:50pm (KEY 0116)
Friday
9:00am–9:50am
(KEY 0125)
Friday
11:00am–11:50am (KEY 0116)
Friday
10:00am–10:50am (KEY 0126)
You must attend your assigned section
TEACHING ASSISTANTS
Chae Mamayek (Sections 0101; 0102; 0104)
2163 LeFrak Hall
Email: mamayekc@umd.edu
OFFICE HOURS
Tuesday
Thursday
By appointment
Alaina De Biasi (Sections 0103; 0105; 0106)
2163 LeFrak Hall
Email: adebiasi@umd.edu
Tuesday
Thursday
By appointment
10:30am – 12:30pm
10:30am – 12:30pm
9:30 am – 12:30pm
11:30am – 12:30pm
COURSE DESCRIPTION
This is an introductory course in descriptive and inferential statistics that focuses on various
ways statistics are utilized in the fields of criminology and criminal justice. The beginning part
of the course concentrates on descriptive statistics, which are utilized to “describe” social
phenomena of interest. The latter part of the course investigates inferential statistics, which are
used to “infer” relationships among different variables of interest, generalizing them to the larger
populations from which study samples are drawn. For instance, if a researcher is interested in
the relationship between gender and crime, he or she might first want to describe this relationship
using descriptive statistics (e.g. X percent of violent offenses are committed by males), before
inferring a relationship between gender and crime (e.g. being male increases the number of
violent crimes committed by X). The goal of this course is to give you the tools necessary to
successfully complete these tasks. All examples will employ crime data and deal with issues in
criminology and criminal justice.
COURSE GOALS AND EXPECTATIONS
The primary goal of this course is to provide you with an understanding of various statistical
concepts commonly utilized in criminology and criminal justice, and to give you the ability to
calculate a variety of common statistical operations. Upon completion of this course, you should
have an understanding of the following statistical concepts and operations:
1) Basic differences in nominal, ordinal, interval, ratio variables, and units of
analysis.
2) Descriptive statistics such as means, medians, mode, variance, and standard
deviation used to numerically describe the central tendency, dispersion, and
skewness of the data.
3) Theoretical differences between sampling and population distributions.
4) The standard normal distribution and the standard normal distribution table.
5) Hypothesis testing using a binomial distribution.
6) Statistical significance/hypothesis tests including:
Z-tests for large samples
T-tests with one mean
T-tests with two means
Chi-Square statistics for categorical data
Measures of association for categorical data
F-tests for three sample means
Bivariate ordinary least squares regression
LEARNING OUTCOMES
This course is designed to foster a student’s ability to apply mathematical formulas, structured
protocols, and analytical patterns of reasoning to examine a variety of different research
questions in criminology and criminal justice. Students will learn to critically analyzing
associations, to assess the strength of statistical evidence, and to draw valid conclusions
regarding mathematical and statistical relationships between variables. The specific learning
outcomes addressed in this course include:
• Distinguishing between raw data and statistical inferences from data
•Understanding appropriate analytical methods for drawing valid statistical conclusions
•Applying appropriate analytical methods to evaluate statistical inferences
•Systematically evaluating statistical evidence for its validity and for alternative explanations
•Using formal analytical and computational techniques to address real-world problems
PREREQUISITES
Math 111 or higher, CCJS 100 or 105. Basic computation skills, some knowledge of probability
theory and facility with a calculator is required. People who lack confidence in their math skills
should review Appendix A in the textbook.
TEXTBOOK
Required: Bachman, R. and R. Paternoster. Statistical Methods for Criminology and Criminal
Justice. McGraw-Hill 2008. 3rd Edition. (ISBN 0073129240)
COURSE GRADING
The ultimate goal of this class is for you to do well on the exams. In particular, doing well on
the final exam will demonstrate that you understand the material in the course. The final is
cumulative and is worth 25% of your grade. In order to do well on the exams, it will be
extremely important that you keep up with the weekly reading, homework, and quiz assignments.
In addition to the homework and quizzes, there will be three examinations throughout the
semester that will last the length of the class. Regular office hours are scheduled throughout the
week to assist you with the material. Your participation in and contributions to lecture and
discussions will be factored into your participation grade. Extra credit assignments are available
at the instructor’s discretion.
Grading Breakdown
Participation 5%
Quizzes
10%
Homework
15%
Exam 1
15%
Exam 2
15%
Exam 3
15%
Final Exam 25%
Final grades will be assigned according to the scale below. Students near grade divisions
(e.g. 89.4%) may have their grade adjusted upward (but not downward) for effort in the
course and participation in the discussion groups.
A
B
C
D
F
A+ = 99.5% - 100%
= 92.5% - 99.49%
A- = 89.5% - 92.49%
B+ = 86.5% - 89.49%
= 82.5% - 86.49%
B- = 79.5% - 82.49%
C+ = 76.5% - 79.49%
= 72.5% - 76.49%
C- = 69.5% - 72.49%
D+ = 66.5% - 69.49%
= 62.5% - 66.49%
D- = 59.5% - 62.49%
= Any grade <59.5%
EXAM POLICY
There will be four exams over the course of the semester: three in-class exams each worth 15%
of your grade, and a cumulative final exam worth 25% of your grade. All assigned material
presented in lecture and in the readings will be covered in the exams. Exams must be taken on
the assigned day unless you have made make-up arrangements prior to the exam, and you can
present a valid, written excuse upon your return. Health center notes are not valid excuses.
Make up exams will be all-essay exams. In the event that you need to miss the final exam, you
must notify Professor Johnson by the date of the second exam. Exemptions for the final exam
may be given at the instructor’s discretion and will be strictly limited to students who earn A’s
on all three examinations and have an A average on both their homework and quiz grades in the
course.
QUIZ POLICY
You have a weekly quiz on the readings available through ELMS (Enterprise Learning
Management System). The quiz questions are taken verbatim from the text and are designed to
encourage you to keep up with the reading. You are allowed 5 minutes to take each quiz, and
you can take each quiz twice. The questions are chosen randomly from a question bank, so you
will not get the same questions the second time around. Please pay attention to the schedule at
the back of this syllabus for when each quiz is due; quizzes will be available to take for 48 hours,
and will close at 12:30pm on the day they are due. You may use your book for the quizzes but
you may not collaborate with anyone else while taking the quiz. Your lowest quiz grade will be
dropped when calculating your final grade. Please print a copy of your submitted quiz for your
own records, and as proof of completion in the event that an error occurs with the ELMS
scoring.
HOMEWORK POLICY
The goal of the homework is to help you practice and stay up with the material. The homework
is available to you on ELMS one week prior to the date it is to be handed in. The following rules
are in place to protect the fairness of the homework process.
1)
Each homework assignment will be worth 20 points. One question from each homework
assignment will be graded at random and it will be worth 10 points. The other questions
will be checked for completion but will not be graded. The remaining 10 points will be
awarded for submitting a completed assignment at the designated time. It is up to you to
check the homework answers to make sure you are completing the homework correctly.
2)
Homework will be handed in at the beginning of your assigned section on the day it is
due. Homework will not be accepted after the beginning of the discussion period. If for
good reason you need to miss a discussion, you may make prior arrangements with your
teaching assistant to hand the homework to him or her personally before discussion. You
may not put it under the door, in a mailbox, have another student turn it in, or otherwise
drop it off without express prior agreement. Please contact your teaching assistant
3)
4)
directly prior to the discussion if you need to miss for a valid reason.
Under no circumstances will homework be accepted late. Late is defined as any time
after the beginning of your assigned discussion section on the due date. The homework
answers are posted at 3 PM on the day each is due, and it would be unfair to the rest of
the students if answers could be written with access to the answer key. This includes
sickness or other problems, with the exception of excused athletic absences. The lowest
homework grade is dropped when calculating final grades, so one missed assignment will
not hurt your grade. Exceptions to this rule will only be made at the discretion of
Professor Johnson in the event of unique extenuating circumstances.
In the case of athletes with legitimate excuses, the student athlete should make
arrangements to give the assignment to the teaching assistant at the earliest possible time.
Athletes are required to furnish written documentation about team related absences as
soon as possible. Please note - we can check if you have accessed the web site after the
answers have been posted and before you handed it in. Doing so violates the academic
integrity of the course and will be dealt with according to university policy.
COURSE RESOURCES – ELMS
This course utilizes a web page tool called ELMS to provide easy access to important course
information. You must be registered in this class and use your Directory ID and password to log
on to the site. This web site will include copies of the syllabus, quizzes, homework assignments,
practice exams, and homework and discussion solutions. The website will also contain class
announcements, which contain information that all students are responsible for knowing! ELMS
also allows you to access your grades once they are posted. We strongly encourage you to
access this web site on a regular basis. The site address for this course is http://elms.umd.edu.
Please refer to the online Quick Tutorials Catalogue to answer questions about functionality.
TUTORING
For students in need of additional assistance, the University of Maryland offers a “Math Success
Program”. Students are welcome to visit the center to get help with this course:
http://www.resnet.umd.edu/programs/math_success/
COURSE EVALUATION
Your participation in the evaluation of courses through CourseEvalUM is a responsibility you
hold as a student member of our academic community. Your feedback is confidential and
important to the improvement of teaching and learning at the university as well as to the tenure
and promotion process. Please go directly to the website (www.courseevalum.umd.edu) to
complete your evaluations. By completing all of your evaluations each semester, you will have
the privilege of accessing online, at Testudo, the evaluation reports for the thousands of courses
for which 70% or more students submitted their evaluations.
ACADEMIC INTEGRITY
Cheating on homework or exams will not be tolerated. Students suspected of misconduct will be
dealt with according to the official printed policy of the University of Maryland.
UNIVERSITY OF MARYLAND HONOR PLEDGE
The University has a nationally recognized Honor Code, administered by the Student Honor
Council. The Student Honor Council proposed and the University Senate approved an Honor
Pledge. The University of Maryland Honor Pledge reads:
“I pledge on my honor that I have not given or received any unauthorized
assistance on this assignment/examination.”
Unless you are specifically advised to the contrary, the Pledge statement should be handwritten
and signed on the front cover of all homework, projects, and other academic assignments
submitted for evaluation in this course. Students who fail to write and sign the pledge will be
asked to confer with Prof. Johnson.
STUDENTS WITH DISABILITIES
If you have a documented disability, please confer with your TA by February 4th, 2014.
DEPARTMENT STATEMENT ON CLASSROOM DISRUPTIONS
The success of this class is dependent not only on my ability to convey new and abstract
concepts and ideas, but also on our ability as a class to work together to create an environment
conducive to learning. As a department and university, we expect the faculty and students to be
prepared for class and to be actively engaged in classroom activities. Unfortunately, disruptive
behaviors in the classroom cheat other students of opportunities to learn. The University of
Maryland's Code of Academic Integrity defines classroom disruption as "behavior a reasonable
person would view as substantially or repeatedly interfering with the conduct of a class." This
includes such things as leaving the classroom repeatedly, making loud and distracting noises, and
pursuing side conversations during the course lecture. Also please note that cell phones are to
be turned off during class. Repeated classroom disruptions will result in being asked to leave
the class and may ultimately affect the grade you receive. Repeated tardiness to class lectures
will also be considered disruptive and may influence your final grade in the course.
FINAL COMMENTS
This course has a reputation of being difficult for some students. It is imperative that you keep
up with weekly readings and assignments in order to do well. If you find yourself falling behind
or struggling with the material, do not hesitate to take advantage of the office hours and help
sessions available to you; don’t let your first visit to our office hours come next semester! My
goal as an instructor and your goal as a student are one and the same – for you to do well in this
course by learning to grasp abstract statistical concepts in a way that allows you to understand
their importance for the field of criminology and criminal justice. We are all in this together, and
our success and or failure depends on our ability to work together.
CCJS 200: Introduction to Statistics for Criminology and Criminal Justice
(Subject to Change as Necessary Throughout the Semester)
Day
Date
Topic/Event
Assigned
Reading
Chapter(s)
Quiz Due
Before
Lecture
Homework
Due at
Discussion
Section One:
Descriptive Statistics
Tuesday
1/28
Course Intro
Validity & Sampling
1
Thursday
1/30
Measurement, Variables, &
Units of Analysis
2
Thurs/Fri
1/30-31
Discussion
1-2
Tuesday
2/4
Interpreting Data Distributions
3
Thursday
2/6
Interpreting Data Distributions
3
Thurs/Fri
2/6-7
Discussion
3
Tuesday
2/11
Measures of Central Tendency
4
Thursday
2/13
Measures of Central Tendency
4
Thurs/Fri
2/13-14
Discussion
4
Tuesday
2/18
Measures of Dispersion
5
Thursday
2/20
Measures of Dispersion
5
Thurs/Fri
2/20-21
Discussion
5
Tuesday
2/25
Class Survey
Chapter 2
Homework #1
(Chapter 2)
Chapter 3
Homework #2
(Chapter 3)
Chapter 4
Homework #3
(Chapter 4)
Chapter 5
Homework #4
(Chapter 5)
FIRST EXAM (Chapters 1-5)
Section Two:
Inferential Statistics with One Variable
Thursday
2/27
Introduction to Probability
6
Thurs/Fri
2/27-28
Discussion
6
Chapter 6,
Quiz 1
Homework #5
(Chapter 6)
Day
Date
Topic/Event
Assigned
Reading
Chapter(s)
Tuesday
3/4
Sampling Distributions and
the Central Limit Theorem
6
Thursday
3/6
The Standard Normal
Distribution
6
Thurs/Fri
3/6-7
Discussion
6
Tuesday
3/11
Estimating Population Means
7
Thursday
3/13
Estimating Confidence
Intervals
7
Thurs/Fri
3/13-14
Discussion
7
Tuesday
3/18
SPRING BREAK – NO
CLASS
Thursday
3/20
SPRING BREAK – NO
CLASS
Thurs/Fri
3/20-21
SPRING BREAK – NO
CLASS
Tuesday
3/25
Confidence Intervals &
Hypothesis Tests for 1 Mean
8
Thursday
3/27
Hypothesis Testing for
Proportions & Percents
8
Thurs/Fri
3/27-28
Discussion
8
Tuesday
4/1
Quiz Due
Before
Lecture
Homework
Due at
Discussion
Chapter 6,
Quiz 2
Homework #6
(Chapter 6)
Chapter 7
Homework #7
(Chapter 7)
Chapter 8
Homework #8
(Chapter 8)
SECOND EXAM (Chapters 6-8)
Section Three:
Inferential Statistics with Two or More Variables
Thursday
4/3
Hypothesis Testing with Two
Categorical Variables - χ2
9
Thurs/Fri
4/3-4
Discussion
9
Tuesday
4/8
Two Categorical Variables:
Measures of Association
9
Thursday
4/10
Hypothesis Testing with Two
Population Means
9/10
Chapter 9
No Homework
Due
Day
Date
Topic/Event
Assigned
Reading
Chapter(s)
Thurs/Fri
4/10-11
Discussion
9/10
Tuesday
4/15
Hypothesis Testing with Two
Population Means
10
Thursday
4/17
Hypothesis Testing with Two
Population Proportions
10
Thurs/Fri
4/17-18
Discussion
10
Tuesday
4/22
Hypothesis Testing with 3 or
more Means (ANOVA)
11
Thursday
4/24
NO CLASS LECTURE
11
Thurs/Fri
4/24-25
NO DISCUSSION
11
Tuesday
4/29
Hypothesis Testing with 3 or
more Means (ANOVA)
11
Thursday
5/1
Hypothesis Testing with 3 or
more Means (ANOVA)
11
Thurs/Fri
5/1-2
Discussion
11
Tuesday
5/6
Thursday
5/8
Intro to Correlation and
OLS Regression
12
Thurs/Fri
5/8-9
Discussion
12
Tuesday
5/13
Final Exam Review
1-12
Tuesday
5/20
Quiz Due
Before
Lecture
Homework
Due at
Discussion
Homework #9
(Chapter 9)
Chapter 10
Homework #10
(Chapter 10)
Chapter 11
No Homework
Due
Homework #11
(Chapter 11)
THIRD EXAM (Chapters 9-11)
No Homework
Due
FINAL EXAM (Cumulative) 1:30pm – 3:30pm
COPYRIGHT
The lectures I deliver in this class and the course materials I create and distribute are protected by federal copyright law as my
original works. My lectures are recorded or delivered from written lectures in order to ensure copyright protection. You are permitted to take
notes of my lectures and to use course materials for your use in this course. You may not record, reproduce, or distribute my lectures/notes for
any commercial purpose without my written consent. Persons who sell or distribute copies or modified copies of my course materials, possess
commercial copies of my notes (i.e. Terpnotes), or assist another person or entity in selling or distributing those materials may be considered in
violation of the University Code of Student Conduct, Part 9(k).