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Spring 2024
Section 03: Registration Number 39611
Section 04: Registration Number 39612
Professor Keith A. Markus
Time:
Section 03: Tuesdays 6:00-8:00 PM
Section 04: Thursdays 6:00-8:00 PM
Room:
Section 03 & 4: L2.72.05NB, 524 W59 Street, New York, NY 10019 USA.
Course Description
"The primary purpose of the course is to educate students about basic [statistical] theories and techniques used in the behavioral sciences. The instructor will briefly review information typically covered in undergraduate statistics, and then introduce more advanced statistical techniques. Upon completion, the student is expected to understand the theoretical underpinnings for the various statistical techniques and the assumptions that data must meet to validly use these statistics. The student will also gain an introduction to computer-based statistical analysis. 30 hours. 3 credits." (from Graduate Bulletin)
Many students enter the course several years after having taken an undergraduate statistics course. Moreover, new material for one topic often precedes review material for another topic in order of logical development. As a consequence, we will "briefly review" introductory material as if it were new material and do so for most of the semester. Nonetheless, from the start, we will cover most of the material in more depth than a typical undergraduate course. We will cover a number of topics not included in a typical introductory course.Computer based statistical analysis will largely be limited to
the use of spreadsheets. This is because we offer another
course entirely devoted to the topic of computer based statistical
analysis (PSY 737). I highly recommend that course to both
thesis and non-thesis students. Other advantages to
spreadsheets include the fact that you can easily look at the
formulas to know exactly what they are doing, spreadsheets can be
tailored to the course, kept simple and focused, and thanks to
open source office suites like Libre Office, you can take them
wherever you go without any need for licenses to use commercial
software. (In contrast, statistical software is typically
designed for users who already have a firm understanding of the
statistics that they are using.)
Course Objectives
1. Students will learn to view psychological phenomena from the
perspective of quantitative stochastic processes.
2. Students will develop linguistic competence in interpreting,
describing, and critically evaluating basic statistical data.
3. Students will gain experience reasoning from and about
numerical data.
Note: It is not possible for this course to cover all of
the statistics that you might need for a thesis. If you plan
on doing a thesis, prepare yourself for the fact that your data
analysis will likely involve at least some statistics not covered
in this course. See Blackboard for a document comparing what
it covered in this course to other benchmarks.
Diversity and Inclusion
Modern statistics are a cultural artifact tracing back to 19th
century Europe but the field has grown to embrace scholarly
contributions from around the world. Statistics has some
ugly episodes in its history, including historical figures
involved in eugenics who also made lasting contributions to the
development of statistics. Nonetheless, progress in
statistics is driven in large part by responding to existing needs
and unsolved problems. As such, the field benefits from
contributions from people who bring diverse perspectives and
experiences to statistics. Most of you are psychology
students seeking careers in psychology that will not involve
becoming professional statisticians. Nonetheless, much large
scale research in psychology involves collaboration between
researchers with expertise in statistics and methodology one the
one hand and researchers with expertise in a particular topic in
psychology on the other hand. The better you understand
statistics, the better you can contribute to such teams and
communicate with others in your field. My intention is for
this course to speak to you and empower you in your career no
matter your background or milieu. Moreover, statistical
methods play a central role documenting injustice or
discrimination and in crafting legislation intended to combat
them. Looking beyond your profession and career, I hope that
a richer understanding of statistical methods will be valuable to
you as an informed citizen and participant in democratic
governance seeking to leave the world better than you found it.
Required Background Knowledge
This course assumes familiarity with basic math and algebra.
Please take the Basic Math and Algebra Screening Test on
Blackboard. Let me know if the questions are unfamiliar to
you or if you find the test difficult. If so, it may be wise
to talk to your program head about taking an undergraduate math
course this term and registering for this course in a later term.
Required Reading
Bachman, R, Paternoster, R. & Wilson, T. H. (2022).
Statistical methods for criminology and criminal justice (5th
ed.). Thousand Oaks, CA: Sage Publications(Caution: If you
rent, make sure that the rental term reaches through finals
week.) Please make sure that you get the 5th edition.
A number of typographical errors have been corrected and some
material has been changed.
Software
I strongly recommend that students install the free office
suite Libre Office and use the Calc spreadsheet program (https://www.libreoffice.org/).
I will also post Microsoft Excel versions of the spreadsheets but
Microsoft is breaking backward compatibility and some of the
features used in the course no longer work in Excel (although they
did when I created them). The programs are very similar, but
there are some important differences.
Such spreadsheet software remains a popular choice for data entry
even among researchers who use more specialized statistical
software for data analysis (the topic of PSY 737). However,
research shows that specialized statistical software can be more
confusing than enlightening when learning fundamental statistical
concepts. Excel/Calc offer a simple computing environment
for working with data ideal for learning and gaining confidence
with fundamental statistical concepts. (Mac users: You
can open both Excel and Calc files using the Mac version of
LibreOffice. However the spreadsheets will not work in
Numbers.) Additional optional software will be explained on
Blackboard. (You will need a computer that is capable of
running locally installed software to complete the
assignments. A digital device that relies entirely on web
applications will not suffice.)
Internet Connection and Learning Management System
Students will need to be able to download files from the learning
management system onto a computer with spreadsheet software
installed. The learning management system is accessible
through the CUNY portal: www.cuny.edu
(see direct link at top right of this document) and works best
with the Mozilla
Firefox browser.
Learning Management System
The learning management system for this course will be
Blackboard. The Spring 2024 term will be the swan song for
Blackboard as the learning management system at John Jay College
of Criminal Justice. However, my understanding is that
Spring 2024 courses will remain accessible for some period beyond
the end of the semester. For more information about the
transition to BrightSpace, see the following web page: https://new.jjay.cuny.edu/academics/online-education/learning-management-system/learning-management-system-transition
Note: Some of you may have become accustomed to relying on the
learning management system to alert you to all deadlines and due
dates. This approach is not recommended for this
course. Please keep a copy (digital or paper) of the
syllabus close at hand throughout the semester. The schedule
on the syllabus is the definitive guide to deadlines and due dates
for the course. I will try to reinforce these on the
learning management system but that is only a secondary
convenience and should not be relied on exclusively.
Class Time
The course design is a partially "flipped classroom". I will
not lecture. Instead, I will post instructional materials
associated with each week on Blackboard for you to use outside of
class. We will use class time to (a) answer your questions,
(b) work on practice problems, (c) review the quizzes and T&F
questions from the presentation slides, and (d) other activities
to help reinforce learning. (However, you will still need to
devote time outside of class to completing assignments.) The
course is designed to help you actively engage with the material
so that you will understand it better and remember it longer.
Do the reading before the corresponding class. If you have
questions about the reading, bring them to class and I will try to
answer them there (ideally by posting them to a discussion board
on the learning management system). I want to leave some
flexibility to use the class time in the manner you will find most
useful. Note, most students find it helpful to read some
materials more than once. Only the first time through the
reading need precede the corresponding class.
Asking effective questions: Try to formulate
questions in an effective manner. If you ask me to explain
some topic, especially a fairly general one, I will probably give
a brief overview and refer you to the appropriate passages from
the textbook or instructional materials. This is not an
effective question (unless that is what you are after) because you
are not giving me clear information about what you do not
understand, leaving me to guess or just duplicate what you can
find elsewhere. If something was unclear to you there, it is
likely to be equally unclear in my answer. Instead, try to
be as specific as you can about what you do not understand.
If you do not understand a particular term, tell me what you find
confusing about it. If you do not understand a particular
sentence or paragraph, cite the passage and explain why it does
not make sense to you. If you are confused about a
particular statistical analysis, explain the step that you find
unclear and what you think that the possible options are.
The more context and detail that you can give me, the better the
chances that I can give an answer that is helpful and informative
to you and to other students in the class with similar questions.
If your question is related to an assignment, phrase your
question in a way that does not involve any spoilers for other
students working on the same assignment. If in doubt, email
me privately rather than directly posting on a discussion
board. I will then paste an anonymized and, if necessary,
edited version of the question and answer to the discussion board.
Feel free to search for answers to your questions on the
Web. However, please do not attempt to post questions
related to the course using online fora like Cross Validated or
Stack Overflow. These are precious resources maintained by
busy people donating their time and expertise. It is not
appropriate to lean on them for questions related to a course when
you have ready access to an instructor. Save that for later
in your career when you are no longer a student. (Also, you
will probably get a terse answer that either refers you to
introductory material or assumes more background knowledge than
you currently have.) You should be able to complete
assignments based on the provided course materials but if you make
use of additional resources be sure to credit them in what you
turn in (see Academic Integrity).
Everyone from me to your class mates are depending on you to ask
questions when you have them. If you have a question, you
can be fairly certain that others have the same question.
Your question is not a "dumb question" but asking the question is
the smartest thing that you can do. Everyone else will
appreciate your having asked the question.
Non-Class Time
I recommend that you begin each week by reading the chapter once
through for the first time. From there, move to the online
instructional materials. These are organized into subtopics
which you can often explore in an order of your choosing.
(My videos often provide an overview of the week's
material.) In many ways, learning statistics is like
learning to skateboard, ride a bike, or bake a cake: You can read
about it from a book but you really need to practice to develop
any skill. So, I strongly recommend taking time to play
around with the spreadsheet calculators provided each week,
plugging in different numbers and trying things out for
yourself. Instructional materials primarily include: (a) pdf
handouts, (b) spreadsheet workbooks and (c) videos. I will
also provide links each week to StatQuest
videos on related topics. Finish the first reading of the
chapter and the instructional materials before class meets.
Use what you learn to complete the Application Assignment and to
formulate questions to ask in class. After class, I
recommend completing the weekly quiz before the start of the next
week, to get it out of the way. I recommend completing at
least one or two Quests prior to taking the quiz because these are
an excellent way to check your understanding of the material and
to gain a deeper understanding of it. Also, Quests take time
and you do not want them to pile up until the week before the
deadline.
Academic Integrity Attestation
This is a non-graded course requirement. No other
assignments will be accepted for credit unless this form is
completed, signed and submitted. The form is available on
the learning management system course page and attests that you
understand the principles of academic integrity and will abide by
them in completing all course work involved in this course.
(See further information near the end of the syllabus.)
Application Assignments
Weekly application assignments will appear on Blackboard in the
folder for each week. See Schedule for
due dates. These will be relatively short assignments
applying the material for that week. You can complete them
in a word processing program (or simple text editor) and upload
the file to Blackboard using the Blackboard Assignment Tool in the
same location. PDF (portable document format) files are
great because special characters are stored internally. I
can probably also open RTF (rich text format), ODT (open document
text), DOC (old Microsoft Office format) and DOCX (new Microsoft
Office format) but these are riskier (e.g., if you use a font I do
not have). If I cannot open a file, or it appears jumbled, I
will accept it as on time but send an email request for a PDF
file. Try to keep up with these and not fall behind but I
will accept late Application Assignments up until the Quest
deadline for each section of the course.
Note: Students sometimes become overconfident and try to complete
Application Assignments before they do the reading. This is
a bad idea. We will cover things you did not learn in your
undergraduate statistics course. If you attempt the
Application Assignments without doing the reading, you will
invariably do a face plant. That will mean that I have to
expend a lot of time and effort giving you written feedback about
what you did wrong, even though by the time I grade the
assignment, you will probably have done the reading and figured
out what you did wrong on your own. This will delay me
returning grades and deny you the opportunity to test your
understanding of the reading when you complete the
assignment. Many of the assignments include extensive
cautions against the kinds of mistakes people make when they have
not done the reading. Always go back and check your answer
against these cautions before you submit your answer. (In
particular, note that we will not talk about testing hypotheses
involving more than one variable until Week 9 of the course!
That means that if you give me an example involving an independent
variable and dependent variable before Week 9, it is going to be a
wrong answer. Keep that in mind. Many of you have been
brainwashed to think that testing associations between independent
and dependent variables is all there is to statistics and you will
need to make an effort to unlearn that.)
Quizzes
Weekly quizzes will comprise six questions. When there are two
chapters, there will be three questions from each chapter.
The quizzes will be available on the learning management system in
the folder for the week that they test (not the week that they are
due!). See Schedule for due dates.
Your total quiz grade is equal to the mean proportion correct
across all quizzes after dropping the two lowest quiz
grades. See the learning management system for a document
providing a more detailed description of quiz items. You
only get one try at a quiz. So, I strongly recommend
completing all other assignments and mastering the material
through further study before taking the quiz. You are
allowed to use your notes, textbook, and other instructional a
materials while taking a quiz, but they are not necessary to
complete the quiz.
Note: We will go over quizzes in class after they are due (in the
second section to reach them). As a result, there can be no
late quizzes. This will be a hard and fast deadline because
delays in going over the quizzes are very disruptive to other
students. If you miss a quiz for some reason, it will be
counted toward the two lowest grades that you can drop (see
grading). If you miss three or more quizzes, the zero grade
will count toward your course grade. So, stay on top of the
deadlines and be sure to complete quizzes before the deadline (see
schedule for specific times of day and dates). Caution: I
discourage waiting until the last minute because if you have not
submitted the quiz by the deadline according to the learning
management system's internal clock, you will be prevented from
ever submitting it even if you have answered all the
questions. Leave yourself time for technical difficulties
with the learning management system or your internet connection
(also the learning management system can sometimes go down
unexpectedly). I recommend turning things in a day before
they are due, but at the very least try to get them in several
hours before the deadline.
Grading
Your final grade comprises your Application Assignment grade, your
Quiz grade, your Quest grade for each of the three parts of the
course, and your Power Up. The Application grade counts each
of the 12 application assignments as 1 point and equals the sum of
these divided by 12. The Quiz grade counts each quiz as 1
point, drops the 2 lowest, and divides the sum by 10. The
Quest grade for each part is the number of quests that you
(successfully) completed (again, not just turned in with
answers). You are required to complete 15 quests for Part 1
and for Part 2, and 12 quests for Part 3. Your final grade
is based on the proportion of the required quests completed in
each part. Specifically, I calculate min(N, F) / N where N
is the minimum required quests (15 or 12) and F the number of
completed quests for that part of the course. The Power Up
is calculated based on extra quests beyond those required.
Here, I calculate max(0, F - N) for each part of the course, add
them together, and divide by 14. As such, you can never
loose points with a negative Power Up, it will never fall below
zero. The Power Up reflects the extra quests you complete
beyond those required for each part of the course (not by
individual chapter). As described above, you can earn the
equivalent of one extra quest by maintaining good
attendance. This will be added into your Power-Up score
prior to computing your grade.
Caution: All of this is contingent on your submitting the
required Academic Integrity Attestation form. I will not
accept assignments or quizzes for a grade without a signed form.
Your Numeric Course Grade is calculated from the above scores as
follows: (.25 * Application Assignments) + (.25 * Quizzes) +
(.17 * Part 1 Quests) + (.17 * Part 2 Quests) + (.16 * Part 3
Quests) + (.05 * Power Up). In words, Applications and
Quizzes both count 25% of your grade, required Quests count for
50%, and you can earn up to 5% extra credit by completing extra
quests. There will be no other extra credit options beyond
Power Ups.
I will use the following chart to convert Numeric Course Grades
to Letter Course Grades. On the proportion (not percent)
scale, I will round .xx5 and above up and anything below .xx5
down.
Letter Grade | Numeric Course Grade |
A | .95-1.00 |
A- | .90-.94 |
B+ | .85-.89 |
B | .80-.84 |
B- | .75-.79 |
C+ | .70-.74 |
C | .65-.69 |
C- | .60-.64 |
F | .00-.59 |
Contact Information:(It usually works best to email me.)
Office Hours:
By appointment. I will dedicate a Blackboard Discussion
Board to questions and check it several times a week. For
anything that you do not want to share with other students,
contact me by email. I can answer many questions quickly by
email (I will post an anonymous version to Blackboard for
course-related questions.)
Office: Room 10.65.04, 524 W59 Street.
Phone: 212-237-8784 Please do not leave messages at this number. (I do not check voice mail when off campus and I no longer receive voicemail as email for some reason.)
Email: KMarkus@aol.com
Week |
Section 03 Tuesday Meeting Dates |
Section 04 Thursdays Meeting Dates |
Assignments All assignments due by 5:PM on the date listed in the meeting dates column unless otherwise noted. |
Reading |
Topics |
1 |
1/30 |
1/25 |
1/25 |
Ch 1 (Recommended, Appendix A) |
Why am I here? What is this class about?
Syllabus. Statistical inference and Sampling. |
2 |
2/6 |
2/1 |
Week 1 Quiz Week 1 Application Week 2 Application (see above note regarding time) |
Ch2-3 |
Levels of measurement, Distributions |
3 |
2/13 |
2/8 |
Week 2 Quiz Week 3 Application |
Ch 4-5 |
Central tendency, Dispersion |
4 |
2/20 |
2/15 |
Week 3 Quiz Chapters 1-5 Quests Deadline (and late Application Assignments for Part I) |
|
|
5 |
2/27 |
2/29 (2/22 follows Monday schedule) |
Week 5 Application |
Ch 6 |
Probability, Hypothesis Testing |
6 |
3/5 |
3/7 |
Week 5 Quiz Week 6 Application |
Ch 7 |
Point estimation, Confidence Intervals |
7 |
3/12 |
3/14 |
Week 6 Quiz Week 7 Application |
Ch 8 |
Single group mean and proportion |
8 |
3/19 |
3/21 |
Week 7 Quiz Week 8 Application |
Ch 9 |
Hypotheses and measures of association with categorical data |
9 |
3/26 |
3/28 |
Week 8 Quiz Week 9 Application |
Ch 10 |
Two group mean and proportion |
10 |
4/2 |
4/4 |
Week 9 Quiz Chapters 6-10 Quests Deadline (and late Application Assignments for Part II) |
||
11 |
4/9 |
4/11 |
Week 11 Application |
Ch 11 |
One-way ANOVA |
12 |
4/16 |
4/18 |
Week 11 Quiz Week 12 Application |
Ch 12 |
Bivariate correlation and regression. |
13 |
5/7 (Spring Recess 4/23 & 4/30) |
5/2 (Spring Recess 4/25) |
Week 12 Quiz Week 13 Application |
Ch 13 |
Multiple regression |
14 |
5/14 |
5/9 |
Week 13 Quiz Week 14 Application |
Ch 14
(http://statpages.org/logistic.html) |
Logistic regression |
15 (Finals week) |
5/21 |
5/16 |
Week 14 Quiz Chapters 11-14 Quests Deadline (and late Application Assignments for Part III) |
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