BioStatisticsAppliedStatField

=** BIO Statistics **=


 * __ HW and files: __ **

HW is at the end of each chapter (there are only 4-6 of them). The detailed solutions are on the course website

Ch6 example of Spearman Ranking is in




 * TOURO COLLEGE COURSE SYLLABUS **

 **LANDER COLLEGE**

 **DEPARTMENT:** Mathematics

 **COURSE TITLE:** BIO Statistics

 **COURSE NUMBER:** MAT 510

 **PREREQUISITES:** MAT 120 (PreCalculus)

 **CREDIT HOURS:** 3

 **DEVELOPER:** Dr. Kaganovskiy

 **LAST UPDATE:** 1/25/2014


 * __ COURSE DESCRIPTION __ **

This course introduces students to a widely applicable contemporary field of Biostatistics, particularly stressing the use of free computer package R, which allows quick and precise way to solve Statistical problems. This discipline is an integral part of contemporary Medicine, Pharmacology, Biology, Ecology, and Agriculture etc... We focus on how to use R to solve real world problems. The course is at the introductory level, with just a basic knowledge of Math (not including Calculus) and basic computing as the only prerequisites. Biomedical examples are drawn from a number of fields including Epidemiology, Bacteriology, Cardiology, Endocrinology, Hematology, Microbiology, Nutrition, Ophthalmology - just to name a few. In addition, a broader sample of examples from Zoology, Ecology, and Demography are presented. The Statistical topics included in the course are Data Analysis, Confidence intervals, Hypothesis testing, Goodness of fit, Linear Correlation and Regression, Analysis of Variance.

The student will:
 * __ COURSE/DEPARTMENTAL OBJECTIVES __ **
 * Learn about R - package in relation to solving real-world problems.
 * Learn about applications of Statistics to problems in Medicine, Biology, Ecology, etc....
 * Learn about Modeling techniques.

This course is intended to teach students the basic concepts of Statistical inference using computer. This should further professional and pre-professional career interests for students in the fields of science and business. Goals include the fostering of analytical and quantitative thinking, and the ability to solve problems and interpret data.
 * __ COURSE/INSTITUTIONAL OBJECTIVES __ **


 * __ HARDWARE/SOFTWARE/MATERIALS REQUIREMENTS: __ **

Freely available R computational packages.


 * __ COURSE REQUIREMENTS __ **

Homework Assignments. Midterm and Final Exams

Individual and group projects.

Students must turn in regular homework as well as longer and more complex projects. Grades are to be based on the weighted average of the grades for projects, homework, and two exams.
 * __ GRADING GUIDELINES __ **

**__ METHODOLOGY __** Classroom lectures and assigned homework problems.

http://www.sagepub.com/dsur/study/default.htm Reduced price digital renting: http://www.coursesmart.com/IR/3314016/9781446258460?__hdv=6.8
 * __ COURSE TEXT __ **
 * A. Field and J. Miles Discovering Statistics Using R.**


 * Additional Textbooks: **

B. Shahbaba "BioStatistics with R" Professor website: [] Book website: []

B. Rosner "Fundamentals of BioStatistics" J. Verzani "Using R for Introductory Statistics"