Additional ArticlesStatistics 302 H Fall 2006 Instructor: James Matis, [email protected] Blocker 404C, 845-3187 Office Hours: MWF 11-12; TuTh 8-9; or by appointment Grader: TBA Prerequisite: Math 141 or 166 or equivalent (i.e., course in finite math with some probability). Text: Principle of Biostatistics, 2nd ed., M. Pagano and K. Gauvreau Notes: Notes are available on the web at stat.tamu.edu/~matis Software: The course will use a statistical software package called SPSS. You are entitled to receive a copy of this package at no additional cost. Details are given at http://software.tamu.edu. Exams: Two in-class exams will be given, tentatively on October 13 and November 10. The final exam will be given as scheduled on Monday, December 11, from 8-10 am. All exams will be closed-book, but you may bring in a page of formulas. Make-up: A student may be excused from an exam only for one of the University-approved reasons (see www.tamu.edu). There will be a general, comprehensive make-up exam for students with approved absences at the end of the semester. Homework: Homework will be assigned on a regular basis. It will be graded and returned. Late homework will receive half credit. Project: An individual project is an integral part of this course. The objectives of this pro-ject include: 1) obtaining data, either from your own research or from some other scientific pa-per from the published literature, 2) applying some statistical procedure introduced in the text, 3) writing an article which addresses the scientific issue and presents your statisti-cal analysis, and 4) giving an oral report of your findings. Grading: The weighting to determine the grade is: Project 25% 3 Exams @ 20% 60% Homework 15% However, a “bounce-back” weighting, where the final accounts for 40% of the grade, with the project, regular exams and homework counting for 20%, 30%, and 10%, respectively, will also be calculated. You will receive the higher of the two weighted scores.• ADA, Plagiarism, and Academic Integrity Statement: TAMU STATEMENT ON DISABILITIES: The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for per-sons with disabilities. Among other things, this legislation requires that all students with dis-abilities be guaranteed a learning environment that provides for reasonable accommodation for their disabilities. If you believe you have a disability requiring an accommodation, please contact the Office of Support Services for Students with Disabilities in Room 126 of the Koldus Student Services Building. The phone number is 845-1637 TAMU STATEMENT ON PLAGIARISM: The handouts used in this course are copy-righted. By “handouts,” I mean all materials generated for this class, which include but are not limited to syllabi, quizzes, exams, lab problems, in-class materials, review sheets, and additional problem sets. Because these materials are copyrighted, you do not have the right to copy the handouts, unless I expressly grant permission. As commonly defined, plagiarism consists of passing off as one’s own ideas, words, writing, etc., which belong to another. In accordance with this definition, you are committing plagiarism if you copy the work of an-other person and turn it in as your own, even if you should have the permission of that per-son. Plagiarism is one of the worst academic sins, for the plagiarist destroys the trust among colleagues without which research cannot be safely communicated. If you have any questions regarding plagiarism, please consult the latest issue of the Texas A&M University Student Rules, under the section “Scholastic Dishonesty.” ACADEMIC INTEGRITY STATEMENT: “An Aggie does not lie, cheat, or steal or tolerate those who do.” For further information on academic integrity, see Honor Council Rules and Procedures at www.tamu.edu/aggiehonor.Syllabus Stat 302-200 Topic # Lectures 1. Data Presentation – data types, tables, graphs (2.1–2.4) 2 2. Summary Statistics – central tendency, dispersion, 2 Chebychev’s inequality and empirical rule (3.1, 3.2, 3.4) 3. Probability Distributions – theory, binomial, normal (7.1, 7.2 2 7.4, 7.5) 4. Sampling Distribution of the Mean – concept, central limit theorem, 2 application (8.1–8.4) 5. Confidence Intervals – two-sided, one-sided, Student’s (9.1–9.4) 2 6. Hypothesis Testing – general, types of errors, power, sample size 3 (10.1–10.7) 7. Comparing Two Means – paired t, two-sample t (11.1–11.3) 2 8. Correlation – scatter plots, correlation coefficients (17.1–17.4) 2 9. Simple Linear Regression – concepts, model, evaluation 4 (18.1–18.4) 10. Inference on Proportions – normal approximation, single proportion 3 concepts, comparing two proportions (14.1-14.7) 11. Contingency Tables – chi-square test, odds ratio (15.1, 15.3) 3 12. Analysis of Variance – one-way ANOVA, multiple comparisons 3 (12.1-12.5) 13. Nonparametric Methods – sign test, signed-rank test, rank sum test 2 (13.1-13.5) 14. Multiple Regression – model, indicator variables, interactions 2 15. Rates – (4.1–4.3) 2 16. Life Tables – computation, application, years lost (5.1–5.4) 217. Sampling Theory – simple random sampling, stratified sampling, 1 cluster sampling (21.1) 18. Supplemental Topics – diagnostic tests (6.4), multiple 2x2 tables (16.1- 1 16.3), logistic regression (20.1), survival analysis (21.1-21.4) ______ 40Milestones for Course Project I. Pre-proposal, due October 4. 1.1 Select some topic and clear it with the instructor. 1.2 Obtain copy of the scientific paper. 1.3 Read paper to decide if you want to pursue the topic. 1.4 Write a paragraph describing the general scientific problem. 1.5 Hand in the paragraph with a copy of the first page of the article as an attachment. Alter-natively, describe your original research problem and data. II. Proposal, due November 1. (20% of grade). This is a written document (not to exceed 5 pages) that: 2.1 Introduces the scientific problem, 2.2 Discusses the previous literature (at least one citation), 2.3 Discusses claims of the paper you selected, 2.4 Describes data (using at least one numerical descriptive measure and at least one graph), and 2.5 Discusses specific aspect of the problem