Basic Statistics for Social Scientists
SOC 294
Syllabus | Fall 2020
Professor
Joanna Pepin, Ph.D.
Email: jpepin@buffalo.edu
Consultation hours: Tuesdays & Thursdays 10:00–11:00am via Discord
TA
Zhe (Rachel) Zhang
Email: Zzhang67@buffalo.edu
Consultation hours: During recitation, 5pm–5:50pm, via Discord
The land on which the University at Buffalo operates is the territory of the Seneca Nation, a member of the Haudenosaunee/Six Nations Confederacy. This territory is covered by The Dish with One Spoon Treaty of Peace and Friendship, a pledge to peaceably share and care for the resources around the Great Lakes. It is also covered by the 1794 Treaty of Canandaigua, between the United States Government and the Six Nations Confederacy, which further affirmed Haudenosaunee land rights and sovereignty in the State of New York. Today, this region is still the home to the Haudenosaunee people, and we are grateful for the opportunity to live, work, and share ideas in this territory.
Course Description
This course will introduce you to the vocabulary, concepts, and statistical techniques used by quantitative social scientists to describe and test hypotheses about the social world.
Statistics are all around you every day—in advertisements, companies try to lure you by claiming the approval of “4 out of 5 experts” or they tout “success rates.” Newspapers report the findings of social scientists on marriage rates and epidemiologists report on the likelihood of disease transmission. Economic decisions at the state and federal level are made on the basis of population statistics, political polls give news pundits talking points, and sports newscasters report the free throw percentages and batting averages of star players. Understanding statistics will make you a more informed citizen and a more intelligent consumer of information.
This is a fully online course with no face-to-face meetings and a few required meeting times (synchronous). The structure of the course is for about 2 modules to be released each week.
Learning Outcomes
What will I learn?
The primary purpose of this course is to increase your statistical literacy data and analysis skills. You will learn how to interpret data and how to choose between different statistical techniques to answer a research question. You will also learn how to compute basic statistics using R. You will practice these skills through weekly assignments, exams, and by producing a final project.
Course Outcomes
| Outcome | Method of Assessment |
|---|---|
| Choose appropriate methods or models for a given problem, using information from observed or deduced data and knowledge of the system being studied. | All learning checks, exams, and lab assignments |
| Employ quantitative methods, mathematical models, statistics, and/or logic to analyze data and solve real-world problems beyond the level of basic algebra. | Lab assignments and final project |
| Identify common mistakes and/or limitations in empirical and deductive reasoning, and in mathematical, quantitative, and/or logical problem solving. | All learning checks and lab assignments |
| Interpret mathematical models, formulas, graphs, and/or tables, to draw inferences from them, and explain these inferences. | Exam 2 and final project |
Materials
- Textbook - Social Statistics for a Diverse Society
- Access to a web-browser with a stable internet connection
- A calculator capable of computing squares and square roots
- A free account with Dicord
- Additional readings will be posted on UBLearns
Technology Recommendations
To effectively participate in this course, regardless of mode of instruction, the University recommends you have access to a Windows or Mac computer with webcam and broadband. Your best opportunity for success in the blended UB course delivery environment (in-person, hybrid, and remote) will require these minimum capabilities listed on this UB website
Schedule
Tutorials: Available by T/R 9:30am.
Recitation: T, 5pm–5:50pm, via Discord
What do I have to attend?
This course is fully remote and a combination of synchronous (scheduled class meeting times) and asynchronous content. The tutorials will be offered on Tuesday and Thursday mornings, but can be completed on your own schedule. Exam reviews and Final Project work days may all take place at scheduled days and times.
Exams must be taken on the day they are noted on the course schedule. The time given to complete an exam will not extend beyond the time allotted (with the exception of a documented accessibility accommodations).
| Week | Day | Date | Topic |
|---|---|---|---|
| 1 | Tuesday | September 1 | Introduction |
| Thursday | September 3 | Research methods | |
| 2 | Tuesday | September 8 | Research methods |
| Thursday | September 10 | Frequency distributions & graphs | |
| 3 | Tuesday | September 15 | Frequency distributions & graphs |
| Thursday | September 17 | Measures of central tendency | |
| 4 | Tuesday | September 22 | Measures of central tendency |
| Thursday | September 24 | Measures of variability | |
| 5 | Tuesday | September 29 | Measures of variability |
| Thursday | October 1 | The normal distribution | |
| 6 | Tuesday | October 6 | Review/Practice |
| Thursday | October 8 | Exam 1 | |
| 7 | Tuesday | October 13 | Sampling |
| Thursday | October 15 | Sampling | |
| 8 | Tuesday | October 20 | Estimation & confidence intervals |
| Thursday | October 22 | Estimation & confidence intervals | |
| 9 | Tuesday | October 27 | Hypothesis testing |
| Thursday | October 29 | Hypothesis testing | |
| 10 | Tuesday | November 3 | Bivariate tables |
| Thursday | November 5 | Bivariate tables | |
| 11 | Tuesday | November 10 | Final Project work day |
| Thursday | November 12 | Review/Practice | |
| 12 | Tuesday | November 17 | Exam 2 |
| Thursday | November 19 | Chi-square & measures of association | |
| 13 | Tuesday | November 24 | Chi-square & measures of association |
| Thursday | November 26 | FALL BREAK | |
| 14 | Tuesday | December 1 | Final Project work day |
| Thursday | December 3 | Regression and correlation | |
| 15 | Tuesday | December 8 | Regression and correlation |
| Thursday | December 10 | Final Project work day | |
| 16 | Thursday | December 17 | Final Project [Due by 11am] |
| Thursday | December 17 | Exam 3 [Due by 11am] Available 12/15 |
Learning Checks 11 and 12 and all Lab Assignments are due Friday, December 11th at 11:59pm.
Requirements
Participation
You will be expected to actively participate in an effort to ensure your understanding of the ideas presented in the course. Your class participation grade will be determined based on your participation in ungraded surveys and discussion platforms throughout the semester. Participation will be measured by completion of surveys/polling embedded in the modules, questions and answers on the course channels (Discord), and engagement during the course recitations. Opportunities to participate will be offered throughout the duration of the course.
Learning Checks
You will complete 12 Learning Checks throughout the semester to check your comprehension of the class material. These will include multiple choice questions, sometimes involve calculations, and at other times you will be asked to provide an interpretive or analytical response.
Your two lowest grades will be dropped from inclusion of your Learning Check grade (even if they are a zero). Suggested deadlines will be given for each Learning Check but they may be turned in up until the point of the exam they correspond with. I will not accept late Learning Checks after this date, as they are intended to help you learn the material to prepare for the exam. Learning Checks 11 and 12 are due at the end of the semester, Friday, December 11th at 11:59pm.
Lab Assignments
You will analyze sociological data using R tutorials that you will be able to access via your web browser. It is strongly recommended that you use a desktop or laptop to complete these labs, as viewing the content on smaller screens will create additional challenges in completing these assignments. Lab Assignments can be (re)submitted until Friday, December 11th at 11:59pm.
Exams
You will take 2 exams over the course of the semester. Although the exams are not specifically cumulative, ability to complete more complex statistical techniques rests on one’s comprehension of earlier concepts.
- Exams must be taken on the day they are noted on the course schedule.
- The time given to complete an exam will not extend beyond the time allotted.
Final Exam
I have decided to offer a cumulative, final exam that you can CHOOSE to take during the final exam period, which will replace your lowest exam score. In other words, I will take your top two exam scores to calculate your final grade. If you are satisfied with your grades from Exam 1 & 2, you do not need to take the final exam.
The final exam for this course is scheduled for Thursday, December 17 at 8:00am. But I will also make the exam available on UBLearns from Tuesday, December 15th at 8am until Thursday, December 17 at 11am if you would like to take it earlier. You will have 90 minutes to answer multiple choice questions. The material will cover all course material, including chi-square and regression (no R coding). Once you begin the exam, you will have to complete it in one sitting.
Final Project
You will apply your new statistical knowledge and coding skills to answer a research question with data. Real world data will be provided to you for your analysis. You will employ your quantitative skills to draw inferences about about a social issue. Final project working days will be used over the course of the semester to develop your project. The skills required to complete the final project will be cumulative. The final project is due December 17th at 11am.
Grading
Grading summary
| Output | Proportion |
|---|---|
| Participation | 5% |
| Learning Checks | 20% |
| Lab Assignments | 25% |
| Exams | 35% |
| Final Project | 15% |
Grading scale (out of 100):
| Grade | Points |
|---|---|
| A | 94.00–100 |
| A- | 90.00–93.99 |
| B+ | 87.00–89.99 |
| B | 84.00–86.99 |
| B- | 80.00–83.99 |
| C+ | 77.00–79.99 |
| C | 74.00–76.99 |
| C- | 70.00–73.99 |
| D | 60.00–69.99 |
| F | 59.99 or below |
The FX grade is given to students who have no course involvement after week 9 of the semester.
How can I succeed?
Statistics can best be thought of as a mix between a language course and a mathematics course. We will begin with simpler concepts and build up toward greater complexity.
Adopting a “growth mindset” will help you get the most out of this course. A growth mindset is the belief that your skills and abilities can develop (through work and practice).
If you have trouble with an early reading, assignment, or exam, I strongly recommend you work to understand your mistakes so that you will not fall further behind. This may include re-reading chapters, revisiting old assignments, forming study groups, and asking the TA for further clarification of concepts.
Be proactive about your performance in this class! Ultimately, your grade is up to you, and is a reflection of your performance. Grades are not assigned based on actual or perceived effort.
It is critical that you remain current with the assigned reading schedule. For every hour that we spend in class, I recommend you set aside two hours for careful reading of the texts, preparation for class, completing assignments, and reviewing your notes.
FAQs
When are assignments due?
Due dates are listed on the course website. Suggested completion dates are given for the Learning Checks and Lab Assignments. I will accept Learning Checks and Lab Assignments until the date of the exam they correspond with. For example, Learning Check 4 will be accepted until the date of the first exam. This is meant to provide a structured schedule for students who want that, but also flexibility over the course of the semester as disruptions are likely to arise.
What is the recitation?
The weekly recitation hour, led by the TA, will include practice exercises (by hand, using spreadsheets, and the R tutorials), review of tutorial material, and opportunities to work on Learning Checks and Lab Assignments, or to study for the exam with the TA’s assistance.
Do you accept late assignments?
Late Learning Checks and Lab Assignments are accepted until the date of the corresponding exam, but will not be accepted afterwards. I strongly recommend you try to adhere to the provided schedule.
As an adult, I understand that you have a lot of other things going on in your life and that you are the one best equipped to decide what merits your time and attention. Sometimes, that isn’t school. And that’s okay. But every decision you make as an adult has adult consequences. I can’t hold each student to different standards than every other student because of the decisions you made.
Will you change my grade?
If you have a question about the grading of any piece of work, first consult with the TA who graded your work. If you cannot resolve your questions with the TA, you should consult with the instructor.
Any questions about grading an assignment or exam must be raised within one week of the date that the work was returned to you. In other words, if you do not review your work in a timely fashion, you may forfeit your right to question the grading of your work.
If you ask for your grade to be changed on any assignment, your grade may be increased OR decreased after the TA or instructor reconsiders your work. Be advised that we err on the side of being too generous, rather than stingy, during the first past of grading. Thus, it is possible that when your paper is re-examined, your grade might be lowered.
Can I do extra credit?
I don’t offer extra credit out of fairness for all students in the course.
Please do not ask for opportunities for extra credit. There are no exceptions.
I appreciate that you are managing competing demands on your time and that you care about your grade.
Instead of spending extra energy completing even more assignments, use it to do your best on the remaining assignments.
What if I need to contact you?
The best way to get in touch with the professor and TA outside of class is through the course discussion channels DISCORD, followed by an email. Please start the email subject line with “SOC294”, and direct emails to the TA first, unless the matter clearly needs the professor’s attention.
Do not expect an immediate response. We will make every effort to respond to emails within 24-48 business hours.
Note, under federal law (FERPA—The Family Educational Rights and Privacy Act), I am prohibited from discussing a student’s grades and academic record with parents.
Academic tip #1 How to address instructors
- Err on the side of formality
- For faculty (with Ph.D.s), use “Professor LastName” or “Dr. LastName” unless directed otherwise.
- Instructors without Ph.D.s usually invite you to use first names (but will likely not be offended if “Professor” slips out).
- Use a formal, respectful writing style
- Include opening and closing salutations (discuss examples).
- No text-speak.
- Do your part in solving what you need to solve.
- Don’t ask about something that’s answered right on the syllabus.
Can I work with others?
You are encouraged to work with your peers in small groups on Learning Checks or Lab Assignments. Remember, however, that working through the tutorials is the best preparation for the exams and Final Project, which you must complete on your own.
Even if you work with others, you must turn in your own Lab Assignments and Learning Checks.
Will you write me a recommendation letter?
Recommendation letters are generally only written for students earning an A- or better in this course.
UB Required Notices
Academic Integrity
Students must be familiar with and abide by the university’s policies and procedures on Academic Integrity, available at: https://catalog.buffalo.edu/policies/integrity.html. In brief, do not cheat. If you are caught cheating on an exam, you will at minimum receive a grade of zero on the exam in question and will be formally reported to the university.
Accessibility Resources
If you have any disability which requires reasonable accommodations to enable you to participate in this course, please contact the Office of Accessibility Resources in 60 Capen Hall, 716-645-2608 and also the instructor of this course during the first week of class. The office will provide you with information and review appropriate arrangements for reasonable accommodations, which can be found at: https://www.buffalo.edu/studentlife/who-we-are/departments/accessibility.html.
Students taking exams with Accessibility Resources must start the exam at the same time/date as the rest of the class unless prior permission has been obtained from the professor.
Incomplete (I) Grades
I do not permit incompletes. If you suspect you will be unable to fulfill course requirements at the level you desire, please resign from the course by the deadline: Nov 13th, 2020.
UB Portfolio
If you are completing this course as part of your UB Curriculum requirements, please select an ‘artifact’ from this course that is representative of your learning and upload it to your UBPortfolio (powered by Digication) account. Templates have been created for this purpose. Artifacts include homework assignments and exams. Your final UB Curriculum requirement, UBC 399: UB Curriculum Capstone, will require you to submit these ‘artifacts’ as you process and reflect on your achievement and growth through the UB Curriculum. For more information, see the UB Curriculum Capstone website: https://www.buffalo.edu/ubcurriculum/capstone.html.
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Please contact UB’s Title IX Coordinator at 716-645-2266 for more information. For confidential assistance, you may also contact a Crisis Services Campus Advocate at 716-796-4399.
Mental Health & Well-being
As a student you may experience a range of issues that can cause barriers to learning or reduce your ability to participate in daily activities. These might include strained relationships, anxiety, high levels of stress, alcohol/drug problems, feeling down, health concerns, or unwanted sexual experiences. Counseling, Health Services, and Health Promotion are here to help with these or other issues you may experience.
You can learn more about these programs and services by contacting:
Counseling Services:
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Health Services:
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Health Promotion:
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Change My Major
Thinking about a Major or Minor in Sociology, Criminology, Social Justice, or Society, Medicine and Health?
To major in sociology, you must:
(a) earn a “C” or better in four required courses: SOC 101 (Introduction to Sociology), SOC 293 (Social Research Methods), SOC 294 (Basic Statistics for Social Sciences), and SOC 349 (Sociological Theory); and (b) complete eight sociology electives, seven of which must be at the 300- or 400-level.
To major in criminology, you must:
(a) earn a “C” or better in six required courses: SOC 101 (Introduction to Sociology), SOC 206 (Social Problems), SOC 293 (Social Research Methods), SOC 294 (Basic Statistics for Social Sciences), SOC 307 (Criminology), SOC 349 (Sociological Theory); and (b) complete six criminology electives at the 300- or 400-level.
To minor in sociology, you must:
(a) earn a “C” or better in SOC 101 (Introduction to Sociology); and (b) complete five additional sociology electives, four of which must be at the 300- or 400-level.
To minor in criminology, you must:
(a) earn a “C” or better in SOC 206 (Social Problems) and SOC 307 (Criminology); and (b) complete four additional criminology electives, three of which must be at the 300- or 400-level.
To minor in social justice, you must:
(a) earn a “C” or better in SOC 206 (Social Problems); (b) complete an internship (SOC 496); and (c) complete four additional social justice electives, three of which must be at the 300- or 400-level.
To minor in society, medicine and health, you must:
(a) earn a “C” or better in SOC 229 (Population Problems) and SOC 322 (Medical Sociology); and (b) complete four additional society, medicine and health electives, three of which must be at the 300- or 400-level.
The Sociology Department also offers a combined BA/MA degree in applied social research. Details about all of our programs can be found on our website (http://sociology.buffalo.edu/undergraduate/).
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