PSYCH-0825-801-FALL25-JOYCE.pdf

Quantitative Methods in the Social Sciences [QMSS]
General Education Quantitative Literacy
Psychology Studies, 0825 (801), Fall 2025

Basic course information
This course fulfills the General Education area Quantitative Literacy.

Meeting time and location
Tuesdays + Thursdays, 08:10 – 10:10 (JST) [2 hours], 303

Instructor information
My name: Dr. Terry Joyce [Terence Andrew Joyce]
My contact information: terry@tuj.temple.edu
My office: 508 (open desk)
Student drop-in hours: I will be available at an open desk in 508 for 30 mins after all classes. However, recognizing that that may not be convenient for everyone, I will also be available between 07:30 - 08:00 prior to all classes. Other times may also be possible by appointment.

Overview of the course

General Education Quantitative Literacy courses present mathematical thinking as a tool for solving everyday problems and as a way of understanding how to represent aspects of a complex world. They are designed to prepare students as citizens and voters to have the ability to think critically about quantitative statements, to recognize when they are misleading or false, and to appreciate how they relate to significant social or political issues. While computation may be part of a Quantitative Literacy course, the primary focus is not computational skills.

Course description: Our understanding of much of reality relies on statistics. Many claims about our world, our society and other societies, specific organizations (such as Temple University), and even our minds and bodies rest on statistical data. Using examples from anthropology, psychology, sociology, political science, and economics, students will examine how social science methods and statistics help us understand the social world. The goal is to become critical consumers of quantitative material that appears in scholarship, the media, and everyday life.

Credit hours: This is a four credit hour course.

Pre-requisite courses: Minimum grade of C- in MATH 0701, MATH 0702, MC3 Y, MC4 Y, MC5 Y, MC6 Y, MC3A Y, MC6A Y, MC3S Y, MC3D Y, MC3O Y, MC3T Y, or MC6T Y

Course learning goals: The core objective of this QMSS course is to foster in students a basic appreciation of how statistics is essential to all areas of social science research. Accordingly, this course shares the following learning goals, which are common to all Quantitative Literacy courses:
• Understand the assumptions of sampling to generalize to a larger population, and the threats to generalization;
• Perform simple computations associated with analyses of social science data such as comparisons of means and analyses of two-way tables and make conclusions based on the results;
• Apply statistical techniques such as central tendency, dispersion, and association to solve problems in the social sciences;
• Understand the various sources of uncertainty and error in social science data like surveys, experiments, and administrative records;
• Link statistical results to ongoing theoretical social science debates.

Course learning outcomes: Upon completing the QMSS course, students should be able to:
• Appropriately organize and represent graphically datasets, using histograms, polygons, and other charts;
• Calculate, for a given dataset, measurements of central tendency (such as mean, medium and mode) and measurements of variability (such as variance and standard deviation), as well as compute, for a given data point, measurements of position (such as z scores and percentiles);
• Articulate the connections between probability, the central limit theorem, and samples and populations;
• Conduct the hypothesis-testing procedure for a z-test (single mean) and for three kinds of t-test (single mean, two independent means, and two dependent means);
• Compute, for a dataset consisting of two variables, the correlation coefficient and, for a dataset consisting of two or more nominal variables, the chi-square test of independence.

Course materials
Required textbook: This course uses OpenStax’s Introductory Statistics 2E textbook; even though the QMSS course diverges from the textbook approach on various aspects and not all its content is covered.
It is possible to access this free textbook in a variety of ways, including view online, download a PDF version, ordering a print copy, or downloads for Bookshare, iBooks and Kindle formats. These can all be found at https://openstax.org/details/books/introductory-statistics

Canvas: QMSS course utilizes Canvas to:
• provide all PDFs (lecture slides) and Excel files (demonstrations) used in class, as well as lecture recordings for Units 5~7,
• administer unit problem sets, and
• track student attendance + post grades for examinations.
Although the basic organization of the Canvas course will be introduced during the first class, if you are unfamiliar with Canvas or ever experience problems using it, I will gladly provide further help and support.

Calculator: As many statistical procedures involve square-root calculations, which are extremely difficult to do manually, students must have a calculator capable of performing square-root calculations for use in the mid-term and final examinations. Without a suitable calculator, students will be unable to complete the course examinations.

Excel: This QMSS course emphasizes the importance of conceptually understanding a set of basic statistical procedures; an understanding that is best gained by manually computing the respective formula. However, as an effective calculator for efficiently computing the target statistics in class and for obtaining the levels of precision required for the unit problem sets, the course also introduces how to use Excel spreadsheets. Please note that some functions are not available with online versions of Excel, so students are strongly encouraged to install a full version of Excel on your computer (Temple University provides all students access to Microsoft Office 365 via the TU Portal).

Accessibility
Any student who has a need for accommodations based on the impact of a documented disability or medical condition should contact Disability Resources and Services (DRS) at tujdrs@tuj.temple.edu to request accommodations and learn more about the resources available to you. If you have a DRS accommodation letter to share with me, or you would like to discuss your accommodations, please contact me as soon as practical. I will work with you and with DRS to coordinate reasonable accommodations for all students with documented disabilities. All discussions related to your accommodations will be confidential. Students can learn more about the accommodation process and pre-register on the TUJ DRS website (https://www.tuj.ac.jp/services/drs). Students may register at any time during the semester, but accommodations are not active until you register, so I recommend doing so as early in the semester as possible.

Resources and support: Sometimes the biggest factors impacting student success are things happening beyond the scope of the individual classroom. Temple provides a wide array of resources both to help you overcome academic challenges and those not directly related to the educational challenges of the course. Please reach out to me if you need help deciding which resources might be right for you.

Course schedule

QMSS course structure: While I generally prefer not to follow any textbook too closely in my courses, reflecting my conviction in the special value of practice problems for learning statistics, the QMSS course draws on the OpenStax (2023) Introductory statistics 2E textbook for its clear explanations of the basic concepts and for its numerous examples and practice problems. However, given that it is not possible, or even appropriate, to attempt to cover all the textbook material, the target content for this QMSS course is organized into eight units.

Syllabus changes: Please note that any changes to the syllabus will be announced in class, posted to Canvas, and notification will also be sent via Temple University email.
Week to week schedule: [S = session; § = section]

Grading and assessment guidelines
Grade percentage breakdown:

Course minimum grade: A grade of “C-“ or better is required to satisfy a General Education requirement.
Assessment summary: The assessments in this course have been created for two reasons: (1) For you to demonstrate your progress towards the learning goals for the course and receive useful feedback and, (2) For you to practice skills and develop ways of thinking that will be of use to you in the future.
Final grade calculation:

Attendance: I believe the best way to learn statistics is through supervised practice in working through problems, and, so, naturally, regular attendance is extremely important. Two points are awarded for each class attended on time (plus 2 bonus points for attending all classes) for a maximum of 50 points. Moreover, if a student misses more than 3 classes, without reasonable justification, they will automatically fail the course. When unable to attend a class, please inform me as soon as possible, either in person or by email (terry@tuj.temple.edu).
Attendance and your health: To achieve course learning goals, students must attend and participate in classes, according to the course requirements. However, if you have tested positive for or are experiencing symptoms of a contagious illness, you should not come to campus or attend in-person classes or activities. It is the student’s responsibility to contact me to create a plan for participation and engagement in the course as soon as you are able to do so, and to make a plan to complete all assignments in a timely fashion.]

Key concept review (KCR): Like all disciplines, QMSS is rich in specialized terminology. To facilitate students in internalizing the most important key concepts, I have created seven lists. After completing a unit, the following class will typically start with a KCR session (although KCRs may be adjusted depending on progress and scheduled midterms), where students are to briefly explain some randomly assigned key concepts. For each KCR list, up to 20 points will be awarded for brief explanations that should seek to both (1) describe the relevant concept or formula and (2) touch on the broader significance or relevance of a key concept.

Unit problem set (UPS): As detailed under the QMSS course structure section (below), the course consists of eight units, including both an introduction to the QMSS course in Unit 1 and a final review, with the remaining six units being divided into three blocks of two units each. Reflecting the emphasis on learning statistics through practice with problems, in addition to in-class practice, there is also a problem set on Canvas for Units 1~7. Utilizing Canvas quizzes, most UPSs are scored automatically, and all allow for multiple attempts, in a form of continuous assessment that contributes substantially to the overall course grade. Past experience indicates that late completion and/or poor performance on the UPSs is often a major factor for students failing this course, so students are strongly encouraged to attempt the UPSs in timely and consistent fashion (although students may submit revised attempts for all UPSs until the start of the final examination).

Final project: The final project for this QMSS consists of four sections that review the main learning goals of the course; namely, (1) descriptive statistics, (2) hypothesis-testing for a t-test of independent means, hypothesis-testing for a t-test of dependent means, and (4) correlation.

Examinations: In attempting to even out the pressures associated with objective final exams, QMSS has two mid-term exams and one final exam. Please note that these will be conducted in class and that the scheduling of the midterm exams will be dependent on course progress, but, provisionally, midterm exam 1 is scheduled for the class session of Tuesday 2 October (covering units 2-3) and mid-term exam 2 is scheduled for class of Tuesday 4 November (covering units 4-5). The final exam will take place Thursday 5 December (covering units 6-7). Please note that alternative tests will not be arranged without permission of the Associate Dean for Undergraduate Studies.
Point allocations for all these course procedures are detailed below, together with indications of their relative percentages for the overall course grade.

Technology guidelines
To participate in this course, you will need the equipment, software, and internet access to reliably use Zoom and Canvas as well as “productivity tools” like word processors and spreadsheet software.
Limited resources are available for students who do not have the technology they need for class. Students with educational technology needs, including no computer or camera or insufficient Wifi access, should submit a Student Technology Assistance Application located in TUPortal and linked from the Dean of Students Support and Resources webpage. The university will endeavor to meet needs, such as with a long-term loan of a laptop or Mifi device, a refurbished computer. Note that there are technology resources available for students, including on-campus computers available for student use, the computer labs and free loaner laptop options are available.
Class recording: Recording of this class is permitted with instructor’s permission, but only for personal use. Dissemination, broadcast, or transmission for non-personal, non-academic use will result in disciplinary action taken under the Student Code of Conduct.

Academic guidelines
Academic freedom: Freedom to teach and freedom to learn are inseparable facets of academic freedom. I have the freedom and responsibility to design and facilitate our learning environment to best achieve the promise of the course as outlined in its official description. You have the responsibility to engage with the course in good faith and freedom from mistreatment when your opinion differs from mine. Note that it is not abuse of this freedom for me to require that you support relevant opinions with clear argumentation and solid evidence. For more on academic freedom, consult the official Temple policy on the matter. (http://policies.temple.edu/getdoc.asp?policy_no=03.70.02]).
Academic integrity: Temple University believes strongly in academic honesty and integrity. Plagiarism and academic cheating are, therefore, prohibited. All work you submit for assessment should be your own efforts. For more on this topic, consult the relevant portions of Temple Bulletin and the Student Conduct Code