SOCY 604: STATISTICAL ANALYSIS

SPRING 2005

Professor: Marina Adler, Ph.D. T.A.: James Kelly Kimani

Office: 232 Public Policy Bldg. Office: 255 Public Policy

Phone: (410) 455.3155 Phone: (410) 455.2089

Office Hours: We 2-3,Th 3-4, and by appointment Office Hours: TBA

E-mail: adler@umbc.edu e-mail: jaki1@umbc.edu

Webpage: http://www.research.umbc.edu/~adler/

COURSE DESCRIPTION AND OBJECTIVES

Every day we encounter statements in the media based on statistical data. For example, we may hear in the UMCP President’s report that “The mean high school grade-point average for incoming UM freshmen ‘has jumped from 3.5 to 3.9 in just five years…’” (see Baltimore Sun, October 30, 2003 – on Blackboard / Course Documents for your review). What does this statement mean and what kinds of evidence support or refute this claim? Does the 3.9 figure mentioned above mean that the average student arriving at UMCP has nearly perfect grades? Not really, because many high schools use grade scales as high as 6 or 7 points (rather than the traditional 4) in advanced classes. Knowledge of ranges, averages and weighted averages can explain how students arrive at college with GPAs well over 4.0. Hence, we are dealing with a numbers interpretation issue rather than with a student quality issue, as we were lead to believe by the report. Understanding statistics helps us evaluate information and the quality of evidence purportedly supporting it. It allows us to ask important questions about what we read in order to assess how meaningful information is and to decide whether we should believe this information. This course hopes to make you more educated and critical consumers of information.

In order to accomplish this, this course emphasizes the development of three fundamental skills:

· calculating basic statistics correctly

· identifying & using appropriate statistical procedures

· interpreting quantitative information accurately

This course is intended to give you a graduate level introduction to social statistics by providing basic training in descriptive and inferential statistics with social science applications. The prerequisite for this course is a graduate level research methodology course. Familiarity with personal computers and SPSS or similar software is assumed. Students will use statistical techniques and SPSS computer software to organize data, test empirical hypotheses, and evaluate evidence. The material covered includes basic concepts related to quantification; frequency distributions; measures of central tendency and dispersion; normal distributions; inferential statistics (hypothesis testing); cross-tabulations; measures of association; and linear regression analysis.

REQUIREMENTS

Readings

Healey, Joseph F. 2005. Statistics. A Tool for Social Research. (7th ed.) Wadsworth Publ. Co. [assignments under Healey]

Norusis, Marja. 2004. SPSS 12.0 Guide to Data Analysis. Upper Saddle River, NJ: Prentice Hall. [assignments under Norusis]

Set of lecture notes available for purchase at the University Bookstore (bring to class each time).

Assignments

Attendance. Attendance is mandatory. You are expected to attend each class and inform us of any scheduling problems. Being present for lectures and classroom exercises is crucial to your success in this course. Students are responsible for all announcements made during class, on Blackboard, or via e-mail. We will assume that (a) you are present, and (b) you check your e-mail regularly. We understand that graduate student life is challenging and we all are busy. But by registering for this graduate class you have voluntarily entered a contract and have committed yourself to completing graduate-level work with all its time requirements (see Preparation section below). You are required to bring a college level calculator (includes various advanced functions) to class and to exams.

Readings. Readings are assigned for each class meeting. We strongly encourage students to complete the assigned readings twice: BEFORE the appropriate lecture and AFTER the material has been covered in class. Familiarity with basic concepts and techniques prior to lecture will enhance your comprehension and your ability to ask sensible questions during class. Reading the material again will reinforce what you have learned and reduce the time you spend on homework and review for exams.

Homework. In order to give you practice, you are expected to work a lot of problems. In addition, completion of homework serves as indicator of your commitment to learning in this class. Throughout the semester, you are expected to complete homework assignments, due on dates indicated on the schedule (also see Policy section below). The homework assignments are in the folder “Homework” on Blackboard under “Assignments”. Do not wait to complete homework until the day before it is due because you will encounter technical difficulties and then it is too late to help you! The T.A. will grade your homework based on the degree of work and effort put into the attempt, not merely by whether your solution is correct. In order to be considered complete, all steps of your calculations have to be shown in your work. Unacceptable (sloppy, incorrect, incomplete) work or work not turned in at due date earns “0" points (no exceptions). We prefer typed homework assignments but will accept clearly legible, clean, carefully handwritten homework as well. There are no extensions on homework unless there are verifiable exceptional circumstances - any homework not turned in on the due date will receive an automatic “0" points (no exceptions).

Computer Work. Part of your homework will involve computer work. You will first learn how statistical techniques are manually derived and later you will be able to use the computer as a tool for analysis. Here the emphasis will be on your ability to produce and interpret the desired computer output properly. Familiarity with SPSS or similar software is assumed. On Blackboard under “Course Documents” is a Powerpoint presentation giving you a brief “SPSS Applied Introduction.” You will use several data sets: GSS2002_SAMPLE2.SAV downloadable from wadsworth.com Healey 7^th ed. Companion website under data (or download from Blackboard under “assignments”); and SALARY.SAV and GSSNET.SAV CD that comes with the Norusis book. The professor and T.A. are available for consultation on logistical computer problems and help with conceptual understanding in our office hours, by appointment, and via e-mail. Nevertheless, neither the professor nor the T.A. will be available for intensive individual math tutoring. If you encounter additional problems, you should seek help from outside tutors or university help staff. It is in your interest to (a) earmark a lot of time for your homework and (b) work with fellow students. Of course helping each other does not mean turning in the same work or doing the work for one another (see Academic Misconduct below)!

Preparation. Consistent with academic standards for graduate courses, in addition to attending class regularly, you should plan to spend at least two hours of preparation for each hour of lecture, on average (2.5 hours x 2 = 5 hours preparation time), excluding class time per week. In preparation for exams you are encouraged to work in groups and solve additional problems from your books. The companion website at wadsworth.com for the Healey book has lots of study help!

Exams

The exams will be closed-book and administered in class. You will be able to bring a sheet with formulas.

Policies

General. Late work is strongly discouraged and late make-up exams are given only with proof of illness or other severe circumstances. It is the responsibility of the student to prepare assigned materials on time and to discuss problems with deadlines with the professor. Exams missed without promptly presenting a valid excuse (contact the professor on the same day as the missed deadline), will be counted as "0" points for the scheduled or make‑up exams (no exceptions). Early make-up exams are given for any legitimate reason. There will be no opportunity to make up missed quizzes. You are responsible for being informed about any scheduling changes or announcements about assignments made in class or via e-mail. It is your responsibility to communicate with the professor or T.A. in person or via e-mail. Plan ahead in completing homework assignments. Please note that some questions are better asked after class or in a session with the T.A. or professor. I encourage you to stop by during my office hours or to make an appointment to discuss your progress. If, at any time during the semester you encounter difficulties or special circumstances, contact us immediately in order to work out solutions as soon as possible. All electronic communication devices (phones, beepers, etc) have to be turned off upon entering the classroom.

Academic Misconduct. By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC’s scholarly community in which everyone’s academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct can result in disciplinary action that may include, but is not limited to, suspension or dismissal. To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook or the UMBC Policies section of the UMBC Directory. Academic misconduct may include, but is not limited to, the following (adapted from UMBC’s policy):

Cheating: Using or attempting to use unauthorized material, information, or study aids in any academic exercise, such as exams, quizzes, papers, homework, etc. That includes copying information from classmates’ papers, homework, exams, quizzes, etc.
Fabrication: Intentional and unauthorized falsification or invention of any information or citation in an academic exercise, such as exams, quizzes, papers, homework, etc.
Facilitating academic dishonesty: Intentionally helping or attempting to help another commit an act of academic dishonesty.
Plagiarism: Representing the words or ideas of another as one’s own in any academic exercise. That means that ANYTIME you use the exact words from a published source (including the internet), you have to put them into quotation marks and attach in parentheses the page number and all biographical source information. If you use the contents of any published source (including the internet) by PARAPHRASING it, you still have to acknowledge it in parentheses. Buying papers on the internet or elsewhere and turning them, or any parts of them, in as one’s own original work constitutes cheating. Turning in a paper that was authored by another person in total or part also constitutes cheating.

EVALUATION

Final grades are determined by the total number of points earned in the course based on three (3) exams, eight (8) homework assignments, and regular attendance of class. The latter is used for the determination of "borderline cases" in the calculation of final grades. A conventional grading scale based on percentages is applied, i.e. 90%-100% is an A, 80%-89.9% is a B, etc. Disregarding points achieved, no student can earn an A if s/he has less than a C on the Final Exam. The points for the final grade are calculated as follows:

3 Exams @ 100 pts = 300

8 Homework @ 25 pts = 200

-----

Total: 500

COURSE SCHEDULE OF TOPICS AND ASSIGNMENTS

Readings are always due on the date they are mentioned in the schedule, i.e. the first readings have to be read by February 10, 2005.

Week 1: February 3

Introduction and goals of course

Review of basic methodological terms, data reduction techniques, and math basics

(Make sure your UMBC computer account is activated and you know your password; access Blackboard)

Go to http://sociology.wadsworth.com under Healey student resources for a math review and other study resources

Week 2: February 10

Measures of central tendency and measures of dispersion

Norusis Chapters 1-5; if not fluent in SPSS do the Tour in Chapter 2 hands-on

Healey Chapter 1 and p. 20-21, Chapter 2 and p. 62-68, Chapter 3 and p. 90-93

Healey Chapter 4 and p.119-122; Appendix F (SPSS intro info); under “Course Documents” is a Powerpoint presentation giving you a brief “SPSS Applied Introduction”; use the GSS2002 data set available at wadsworth.com or on Blackboard (you should download this), look at the codebook in Appendix G and practice SPSS (you don’t have to turn in any output now)