Time:
 Section 04: Tuesdays 6:00-8:00 PM


Room:
  Section 04: 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)

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.
4. Students will dispel misconceptions about statistics.

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 General Handouts available on Learning Management System (LMS) 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 the LMS.  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.

If you would find it helpful to have an additional perspective on the material, I recommend Gonnick, L. & Smith, W. (1993).  The cartoon guide to statistics.  New York:  Harpercollins.  I have put a copy on reserve at the Lloyd Sealy Library.  This is a supplement, not a substitute for assigned readings.  I have not pre-ordered this book at the book store.  However, I am happy to answer questions drawn from it in course Q&A forums.

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.  Spreadsheets like Calc and Excel 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.  Please post only ods or xls/xlsx files.  Do not submit either Numbers files (because I cannot open them) or pdf files (because I cannot see inside cells).

Make sure your spreadsheet software is set to display zeros, and does not round the scores.  (In calc: Tools > Options > LibreOfficeCalc > View, then check "Zero Values".  Tools > Options > LibreOfficeCalc > Calculate, then uncheck "limit decimals for general number format".)  Additional optional software will be explained on the LMS.  (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.

The learning management system for this course will be Brightspace.  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.  I am still getting used to the new system.  So, if something does not look right, please ask about it.

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 the LMS for you to use outside of class.  These hold the advantage that you can work through them at your own pace and backtrack any time you do not understand something.  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 LMS, 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, many students find it helpful to read some materials more than once.  Only the first time through the reading need precede the corresponding class.  (If you find it hard to absorb the material from the chapters, you may find it helpful to use the Active Reader Worksheets available on the LMS in the weekly folders.)

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 or aspect that you find unclear and what you think that the possible options are.  If something does not seem right to you, try to give a concrete counter-example.  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.  Never post answers to a 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 (and a tutor).  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, including generative AI (see Academic Integrity).

Everyone from me to your classmates 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 and understanding.  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.  As supplementary materials, 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 the learning management system in the module 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 the learning management system using the assignment tool in the same location.  (If you prefer to do them by hand and upload a scan of the paper copy, that is okay too.)  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 frequently do a face plant.  That will mean that you get less out of the assignment.  (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.)  On the other hand, if you do not understand what something in an assignment means, post a question in time for me to answer it before the deadline.  I have learned the hard way that it is not possible for me to provide individual feedback on Application Assignments and keep up with my other job responsibilities.  So, I will post to the LMS general feedback for the entire class.  If you have a question about an Application Assignment that is not answered in my feedback, please ask.

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 module 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.  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, add your attendance score, and divide by 14 (i.e., 5 + 5 + 4).  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 do my best to disable the incorrect grades calculated by the LMS, the LMS cannot read the syllabus, so please ignore any display that I cannot disable.  I will return grades for each part of the course by (a) posting a pdf file to the LMS that explains what each field means (I will provided each component, not just the final grade, so please read this document first), (b) adding the computed grade fields to the end of the LMS gradebook, and (c) posting an announcement on the LMS indicating that grades are up.

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.

Contact Information:  (It usually works best to email me.)

  Office Hours:  Tuesdays 4-5pm or by appointment.  An appointment is highly recommended.  I will dedicate a LMS 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 the LMS 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