Course Description: Quantitative Research Methods and Analysis is the second course in the two-course methods/statistics sequence. Students enrolled in this course must have taken Soc 2155 and earned a grade of at least "C." This course reviews and extends student knowledge of the statistics commonly used in sociology and criminology research. Specifically, the course covers:

• The organization of quantitative data (e.g., tables, graphs).
• Methods for summarizing and/or describing data with respect to central tendency, dispersion, and association.
• The appropriate use of standard inferential procedures in order to make generalizations from sample data to a larger population.
• An introduction to the use of statistical control.
• The use of statistical software to perform data analysis.

Beyond quantitative data analysis, this course deals with issues related to research methods. This is because statistics and research methods are intimately related. Therefore, while much of the course material will be new, you should have already been exposed to some topics (e.g., levels of measurement, hypothesis testing, sampling, modes of observation). Indeed, this course demonstrates the ways in which research methods and statistics are related.

Upon completion of this course, you should:

• Understand the logic of scientific explanation, including the relationship between theory and research.
• Be able to use statistical analyses to answer sociological and criminological research questions.
  • Be able to perform data analysis on SPSS and to interpret the results.
  • To understand and apply the appropriate measurement of variables, including levels of measurement.
• Be a better consumer of statistics and social science research.
  • Be able to critically assess statistically-based arguments by sources ranging from scientific journals to mass media outlets.
• Understand the necessity for and logic behind statistical control.
  • Be able to analyze relationships utilizing basic statistical control

Special arrangements/Facilities: It is the policy and practice of the University of Minnesota Duluth to create inclusive learning environments for all students, including students with disabilities.  If there are aspects of this course that result in barriers to your inclusion or your ability to meet course requirements – such as time limited exams, inaccessible web content, or the use of non-captioned videos – please notify the instructor as soon as possible.  You are also encouraged to contact the Office of Disability Resources to discuss and arrange reasonable accommodations.   Please call 218-726-6130 or visit the DR website at www.d.umn.edu/access for more information. 

Academic Dishonesty(Cheating): Cheating on exams or assignments will be dealt with in accordance with University policies. Anyone caught cheating on an exam will receive a zero for that exam. Plagiarism refers to presenting another's words or ideas as if they were your own. It is cheating and thus an academic offense. Penalties for plagiarism depend upon the seriousness of the offense, and range from point deductions to failure for that particular assignment.

Attendance/Tardiness: I do not take attendance and there is no formal penalty for missing class (no points will be deducted from your score based solely on attendance). However, past experience with teaching this class suggests that a student's attendance is strongly related to his or her exam performance. Some of the material we cover is very complex, and the lectures are designed to help you organize and comprehend the text. Some things covered in class may not even be in the course readings. Because statistical knowledge is cumulative, one missed lecture (if the material is sufficiently critical and complex) can hurt students for the remainder of the semester. Finally, there will be some in-class assignments that constitute 5% of your grade.

Student Behavior: Given that attendance is not mandatory, I expect students who attend class to pay attention and refrain from passing notes, holding side discussion or engaging in other high school antics. Please turn off you cell phone prior to class. Even with your uncanny texting abilities, it is still very obvious when you are texting under the desks. Given the lab setting of this course, I expect students to listen and contribute to class rather than checking email or face book on the computers. Students who engage in inappropriate behavior will be asked to leave the classroom.

Missed Exams: All students are expected to take the exams on the scheduled date. If you have a legitimate excuse, you must notify me before the exam. Anyone missing an exam without prior notification will receive a zero for that exam.

Late assignments/papers: All students are expected to turn in assignments on the scheduled date prior to the lecture. It is unfair to the students who turn their work in on time to allow others extra time, or to accept late assignments without penalty. Therefore, material turned in late will be docked points. The amount of deduction increases with time.

Student Responsibilities
Each semester, a few students stop by my office (typically after doing poorly on an exam) to ask what they can do to improve. In a nutshell, here is my response:

1. READ THE MATERIAL in the book BEFORE it is discussed in class. The lectures will be much more useful if you follow this suggestion.
2. ASK QUESTIONS in class. Don't assume that the issue is trivial or that everyone else knows the answer. Odds are that if you have a question, others in class have the same question.
3. DO YOUR HOMEWORK ON TIME (or better yet, early). Each semester students who do fairly well on exams nevertheless fail the course because they do not stay on top of the homework. Doing the homework early allows time to ask me or fellow students questions if you run into trouble.
4. COME TO MY OFFICE or call or email if you have having trouble and you have made an honest attempt to understand something on your own. I am more than willing to meet outside of class during my office hours or another arranged time.

Course Requirements:

Exams: There will be three exams. Exams will generally consist of short essay questions, term definitions, and the interpretation of SPSS output.

Assignments: There will be a variety of take home assignments throughout the semester. The assignments generally include problem solving using statistics, SPSS data analysis and/or interpretation, and the analysis of social science articles. Because the assignments vary on length and difficulty they are worth varying levels of credit. The number of points that an assignment is worth will be listed at the top of the assignment. Assignments will either be posted online or handed out during class. Throughout the semester, we will have some in-class assignments. In-class assignments may not be made up.

Final Project: The culmination of this class is a research paper that utilizes techniques of quantitative analysis, including multivariate analysis, to explore a research question that is sociologically or criminologically meaningful. In most cases, this will mean a secondary analysis of data originally generated by someone else. We will be learning in this course how to access the many survey data sets maintained by the Inter-University Consortium for Political and Social Research (ICPSR). If you are proposing to carry out original research (not a secondary analysis, in other words) you will have to choose a topic and get to work early in the semester in order to have time to go through the Human Subjects process, as well as the survey itself and its analysis. Detailed requirements for the final project will be provided at a later date.