Instructor: Aleta Top
Office: Faner Hall 3427
Office Phone: (618) 453-7624
Office Hours: Tuesday 1-1:50, 4-6; Wednesday 1-3; Thursday 1-1:50
Email: gradstudentaleta@yahoo.com

Class Time: 2 - 3:50, Tuesday and Thursday
Class Location: Parkinson 107

Required Book: Levin, Jack and James Allen Fox: Elementary Statistics for Social Research. The sixth, seventh, eight or ninth edition will be fine.

Course Description and Objectives: In a very general way, the word “statistics” refers to the numerical manipulation of information, or what we call “data.” The statistical approach to understanding data results in some form of simplification –reducing an assortment of people’ ages to a single value, the average, for example. Typically, the data are often further analyzed by the statistician using many other complex statistical tests. It will be your task in this course to learn to calculate and interpret the results of these complex forms of analysis (by hand and by computer).
There are three goals for this course. The first is to provide the student with the skills necessary to understand and use many contemporary statistical procedures. By the end of this course, students should understand how to calculate these statistics by hand and through the use of the Statistical Package for the Social Sciences (SPSS – v. 10.0). But, being able to compute a statistics is like being able to spell a word. In each case, one may not know its meaning. It is crucial that the student understands what the statistic is saying. As a result, the interpretation of these statistics will be continually stressed throughout this course. In terms of grading, interpretation will be weighted as heavily as calculation. Finally, it is hoped that the student will feel capable of reading and understanding articles of a professional nature wherein much of what is reported is statistical.

Course Requirements: Four term exams, a comprehensive final, and four SPSS (V10.0) assignments. I will be very strict about late assignments, missed exams and so on. So assume the responsibility of getting your work in on time and taking the exams on the scheduled dates.

Term Exams: Each term exam will focus on material covered in lecture as well as material covered in assigned readings (assigned readings are either chapters of the text or one or two outside readings that I make available). Therefore as might expect, it is to your benefit to read all of the assigned reading material closely, and attend class regularly. These exams will be administered in class, and they will be closed book and closed note. Note the dates of the exams. If you already know that you cannot make several of these dates, you should drop the course. Make up exams are only give for the first three term exams. A make-up exam is only given with the student has a valid excuse. For illness I require a doctor’s note or receipt of services. Family emergencies, legal, scholastic, and athletic reasons will be approved by me on a case-by-case basis. I prefer that I be notified before the missed class date (unless an emergency). Any make-up exams will be given during class one week later in either 3410 Faner Hall or the departmental office. If you miss the make-up exam, you are out of luck. There are no make-up exams for the make-up exams, fourth term exam of final exam.
Each term exam is worth a total of 100 points. However, I will allow you to drop your lowest term exam score. Thus, a total of 300 points can be earned from the term exams (a total of 50% of you course grade). I will also offer you a very attractive offer: if you score at least a “C” on all four term exams, you may skip the final (also worth a total of 100 points). I will substitute the average of your best three term exams scores for your final exam score in computing your grade for the course.

Final Exam: worth 100 points, and it will be cumulative, covering the whole course – which is quite a lot of material, so it is best to avoid it by doing well on the term exams.

Homework Assignments: Because of the nature of this course, you may expect regular homework assignments. A large portion of these homework assignments come from the book and will not e graded. Primarily, there are your responsibility . . . I will no nag to you to complete them. If you did not consistently work the assignments in the back of each chapter, you will not do well on the exams. If is to your benefit to complete these upgraded assignments, because many of the questions will look similar to those on the exam. Four of these homework assignments, however, are graded. Each is work 50 points and must be completed and turned in on the date specified (see course schedule). Homework will be accepted late, but without a valid excuse (illness, personal crises/problems, etc.) 10 points will be deducted for each class day that the assignment is late. Any assignment that is over two weeks late will not be accepted for any reason.

Student Code of Conduct (plagiarism and cheating): I expect that you will maintain the highest standards of intellectual honest in this class. Anyone involved in any act of academic dishonesty as outlined by the University’s Student Code of Conduct will automatically fail the course, and will be asked to leave for the duration of the semester. Plagiarism can result in a failing grade for the project and, possibly, the course.

Grades: Grades for this course are determined by the number of points that you have accumulated throughout the course (total of 600 possible from term exams, final exam, and homework assignments). The grading scale breaks down as follows:

A = 540 to 600 pts. (90% to 100%)
B = 455 to 539.99 pts. (76% to about 89%)
C = 390 to 454.99 pts. (65% to 75%)
D = 300 to 389.99 pts. (50% to about 64%)
F = 299.99 points or below (about 49% or less)

Attendance Policy: Attendance is very important for success in this class. Attendance is not required, but I will be taking attendance for my own personal records. You are responsible for any announcements or assignments made in class, whether you are there or not. Further, the exams will concentrate on material I cover in lecture, so it pays to be in class.

Incompletes: Incompletes are not automatically available in this course. To be eligible for an incomplete you must (1) have completed the majority of course work, (2) be earning a passing grade, (3) be able to document a reason beyond your control that you cannot complete the work in the allotted time, and (4) make formal arrangement with me for when you plan to make up the course work. The reason for the incomplete must be a situation beyond your control. Suddenly realizing that you have spent too much time slacking off during the semester and this class might threaten your graduation status or your GPA is not something beyond your control.

I will be available during office hours or by appointment. I am here to help you. If you have any questions please feel free to drop by or send me an email. Email is often the easiest way to reach me. I check it often, even during the weekend. I am happy to answer any questions that you might have.

Course Schedule

August 20: Introduction to the syllabus

August 22: Chapter 1 and 2
Central issues in lecture: levels of measurement, organizing data (frequency distributions), ratios, rates, and rates of change.

August 27: Chapter 2
Central issues in lecture: percentile and cross tabulation.

August 29: Chapter 3
Central issues in lecture: measures of central tendency (mean, median and mode).

September 3 - 5: Chapter 4
Central issues in lecture: measures of dispersion (range, mean deviation, standard deviation, variance).

September 10: Review

September 12: First Term Exam

September 17: Lab Day
Topics covered: inputting data into SPSS, using SPSS to create (1) frequency distributions, (2) crosstabs, (3) calculate descriptive statistics, (4) graphical representation of data; using select if statements, recode statements, and computing new variables.
Homework Assignment #1 assigned

September 19 - 24: Chapter 5
Central issues in lecture: probability theory; calculating probability; probability distributions; the z-distribution; the mean and standard deviation of a probability distribution; the normal curve as a probability distribution; applying the normal curve to a set of data.

September 24: Homework Assignment # 1 due

September 26 - October 1: Chapter 6
Central issues in lecture: Samples and Populations; sampling methods; sampling error; reducing sampling error; sampling distribution of means; standard error of the mean; confidence intervals; the t-distribution; calculating confidence intervals using the t-distribution; estimating proportions.

October 3: Review Day

October 8: Second Term Exam

October 10 - 15: Chapter 7
Central issues in lecture: using the t-distribution to test the differences between means; sampling distribution of differences between means; independent group t-tests; type 1 and type 2 errors; repeated measures t-test; tests of proportions.

October 17: Chapter 8
Central issues in lecture: one-way analysis of variance; Tukey’s test of honestly significant differences.

October 22: Second Lab day
Topics covered: using SPSS to run t-tests and one-way analysis of variance.
Homework Assignment #2 assigned.

October 24: Outside reading – Spatz: Factorial Design, available in Sociology department office for check out.
Central issues in lecture: two-way analysis of variance (factorial design).

October 24: Homework two is due.

October 29: Chapter 9
Central issues in lecture: nonparametric tests of significance: Kruskal-Wallis one-way analysis of variance; Mann-Whitney U Test; chi-square analysis

October 31: Third Term Exam

November 5: Third Lab day
Topics covered: using SPSS to run nonparametric tests of significance.
Homework Assignment #3 assigned.

November 7: Chapter 10
Central issues in lecture: parametric correlation (Pearson’s Product Moment Correlation Coefficient); zero order and partial correlations.

November 7: Homework #3 is due.

November 12 - 14: Chapter 11
Central issues in lecture: bivariate regression analysis; multiple regression analysis; choosing the appropriate test.

November 19: Chapter 12
Central issues in lecture: nonparametric measures of correlation: phi, contingency coefficient, Cramer’s V; lambda, gamma, Somer’s D; three-way crosstabulation (elaboration).

November 21: Flex day

November 26-28: Thanksgiving Vacation, No class

December 3: Fourth Lab Day
Topics covered: using SPSS to run parametric correlations, bivarate, and multiple regression analysis.
Homework #4 assigned

December 5: Chapter 13
Central issues in lecture: choosing the appropriate test.

December 5: Homework #4 due.

December 9-13: Finals week
Final Exam December 10, Tuesday, 7:50-9:50am