Y502 | 6237 | John Hansen

This is a course designed primarily for advanced graduate students who anticipate future applications of quantitative analysis techniques. Topics covered in this course include a brief review of descriptive of statistics, and a more in depth discussion of hypothesis testing, correlation techniques, regression, comparisons of means (t-test, one-way and two-way analysis of variance). Prerequisite of this course is successful completion of Y520 or P501 or equivalent. Objectives 1.To acquire basic skills necessary for applying statistical principles of inference to well-defined behavioral and educational problems. 2.To be able to objectively evaluate manuscripts in which analysis techniques covered in this course were used. 3.To carry out numerical analyses of data by hand and to use, read and interpret SPSS data applications and output in the Windows environment. Textbook Required: Kirk, R. E. (1999). Statistics: An Introduction (4th ed.), Orlando, FL: Harcourt Brace & Company. Optional: Green, S. B., Salkind, N. J., Akey, T. M. (2000) Using SPSS for the Windows: Analyzing and Understanding Data, (2nd ed.), Upper Saddle River, NJ: Prentice Hall. ISBN: 0-13-020840-X or Green, S. B. & Salkind, N. J. (2003) Using SPSS for the Windows and Macintosh: Analyzing and Understanding Data, (3rd ed.), Prentice Hall. ISBN: 0-13-099004-3 Assignments, Exams, and Laboratory For each topic covered in this course, practice problems and readings taken from Kirk will be assigned. Problems listed on the Chapter Readings have corresponding solutions at the back of the text. For students wishing to work additional problems at the end of each chapter, solutions can be found in the Kirk Instructor Manual on reserve in the School of Education library. Students are expected to be up-to-date on the readings and problems since class time is structured around in-depth understanding of statistical concepts. Constant practice is essential for success in statistics. The utility and language of statistics will come only with practice. You will be required to take three in-class exams as well as complete three take-home assignments. Ordinarily the take-home exam is assigned on the same day as the in-class exam allowing one week for students to complete the take-home questions. You should have a valid student account on the university computing system. This account will facilitate our communication via the e-mail utility and enable you to retrieve reading lists and course lecture notes from Oncourse. Each registered student should be able to access Oncourse at: http://oncourse.iu.edu Login using your IU userID and password. Laboratory attendance each Monday is a required part of the course. SPSS operations and exercises will be an integral part of the learning experience. In the laboratory we will address real research questions with datasets too large to compute by hand. Students will expected to read and interpret SPSS output and can expect exam and take-home assignments to address laboratory components. In past courses we have found that many “Ah ha!” moments occur during lab. Additionally articles used for class can be found and printed from the library electronic reserve: http://ereserves.indiana.edu/coursepage.asp?cid=378 Password: edstats. Grading System Student’s performance in this course will be evaluated based on three required exams. Each exam contributes to 30% of the grade. Lab quizzes and lab work will be incorporated into each of the three exams. Additionally two article critiques will contribute to 10% of the final grade. A final course grade will be determined for each student according to the following mastery levels: 90% mastery or above -- A 87% to 89% -- A- 84% to 86% -- B + 80% to 83% -- B 77% to 79% -- B- 74% to 76% -- C + 70% to 73% -- C 67% to 69% -- C- below 67 = D below 57 = F Incomplete will be given only for a legitimate reason as outlined in the university's Academic Guide, and only after a conference between the instructor and the student. Throughout the course of this section, you may contest every grade awarded to your exams or the overall course performance within 48 hours of receiving such a grade. Once this "statute of limitation" has passed, it is assumed that you willingly accept the grade(s) assigned without further dispute. Academic Honesty and Intellectual Integrity According to P.72 of the Academic Handbook (June 1992 edition), each faculty member has "a responsibility to foster the intellectual honesty as well as the intellectual development of his/her students." In order to achieve these goals, each student enrolled in this course is prohibited from engaging in any form of "cheating" or "plagiarism." Cheating is defined as "dishonesty of any kind with respect to examination, course assignments, alteration of records, or illegal possession of examinations" (p. 72 of the Academic Handbook). "It is the responsibility of the student not only to abstain from cheating but, in addition, to avoid the appearance of cheating and to guard against making it possible for others to cheat. Any student who helps another student to cheat is as guilty of cheating as the student he or she assists. The student also should do everything possible to induce respect for the examining process and for honesty in the performance of assigned tasks in or out of class." (p. 72 of Academic Handbook). Plagiarism is defined as "offering the work of someone else as one's own" (p. 72 of Academic Handbook). "The language or ideas thus taken from another may range from isolated formulas, sentences, or paragraphs to entire articles copied from books, periodicals, speeches, or the writings of other students. The offering of materials assembled or collected by others in the form of projects or collections without acknowledgment also is considered plagiarism. Any student who fails to give credit for ideas or materials taken from another source is guilty of plagiarism." (p.72 of Academic Handbook). Evidence of student academic misconduct will result in (a) a lowered course grade, (b) transfer out of this course, (c) dismissal from student's academic unit, or (d) other disciplinary actions in accordance with the guidelines outlined on p.73 of Academic Handbook. Tips for Successful Learning in Y502 (or any statistics course) For each hour in the class plan on spending 2-3 hours in reviewing/previewing materials. Establish a good study habit by following these steps: Preview materials before coming to each class on Monday and Wednesday; Review materials or recopy notes immediately after each lecture or lab. Talk about lecture / homework problems with study partner. Always bring three things to class/lab: The textbook by Kirk. A functional calculator comparable to Casio model fx260. All notes and handouts ever distributed in class; preferably already organized in a three-ring notebook form. Don’t be shy about asking questions, either directly in class or through email. The instructor’s role is to help you learn and understand the material. Asking questions gives the instructor a chance to detect “problem” areas and try to facilitate the learning process for you and for other students. If you find it helpful, work closely with one or two of your classmates and verbalize your understanding, such as the logic behind hypothesis testing. But don’t become overly dependent on a classmate or friend to answer your questions. Ultimately, learning is an individual responsibility; there will be activities/situations in which you will have to engage in alone. About the exams, (a) forget about cramming the night or the week before; this habit only immobilizes you and convinces you that you “can’t do statistics”; (b) exams are always cumulative because of the nature of materials tested; and (c) the textbook is not meant for casual reading, it must be read slowly at least three or four times before it makes sense. Remember, this course is for you. I will try my best to answer your questions or find the appropriate resources that can. We need to work together to reach our goal -- your understanding of the material. Reading lists and lecture notes can be found on Oncourse and should be printed out by each student before each class. Each weeks lecture notes will ordinarily be available the Sunday before class. Teaching is a dynamic process and I almost always revise my notes relative to the class’s needs. Course materials are posted on Oncourse: http://oncourse.iu.edu Login using your IU userID and password. Additionally articles used for class can be found and printed from the library electronic reserve: http://ereserves.indiana.edu/coursepage.asp?cid=378 Password: edstats. Week Lecture Topics Readings 1 9/1 – 9/5 Course orientation. Math background quiz. Review of fundamental concepts (scales of measurement, variables, summation). Basics of data organization: charts, graphs, distributions. Ch. 1, 2 2 9/8 – 9/12 Central tendency, Variability (range, interquartile range, standard deviation, variance). Box plot. Ch. 3, 4 3 9/15 – 9/19 Probability, Rectangular distribution, Normal distribution, Standard scores, Sampling distribution, Central limit theorem, Standard error. Ch. 8, 9* 4 9/22 – 9/26 Correlation Ch. 5 5 9/29 – 10/3 Regression Ch. 6 6 10/6 – 10/10 Exam 1 (Monday Oct 6th) / Flex Day 7 10/13 – 10/17 Hypothesis testing, One sample t-test, (one and two-tailed), Type I and Type II error. Statistical Inference.Ch. 10 8 10/20 – 10/24 Hypothesis testing, á and p, power, confidence intervals, practical significance. Ch. 10 9 10/27 – 10/31 Student’s t-distribution, Degrees of freedom, One sample t-test unknown population variance, t-test for a correlation. Ch. 11 10 11/3 – 11/7 Two sample t-test independent sample, Two sample t-test dependent sample. Exam 2 (Monday November 10th) Ch. 12 11 11/10 – 11/14 Exam 2 (Monday November 10th) /Flex Day 12 11/17 – 11/21 One-way Analysis of Variance. F- distribution, sums of squared deviations, F-test, Tukey HSD post-hoc test. Ch. 14 13 11/24 – 11/28 One-way Analysis of Variance. Assumptions of ANOVA. Thanksgiving recess no class 11/26. Ch. 14 14 12/1 – 12/5 Two-way (factorial) Analysis of Variance. Main effect, interaction effect. Ch. 15 15 12/8 – 12/12 Two-way (factorial) Analysis of Variance. Graphing and interpretation of interactions. Ch. 15 16 12/15 – 12/19 Final Time / Place TBA * Chapter 9 is the most important chapter in this statistics course. Note: This is a tentative course schedule which is subject to change without prior notice. Changes to the syllabus depend on the pace of classroom instruction an students’ learning needs. Changes will be communicated to each enrolled student via e-mail.