Biostatistics for Public Health Spring Semester 2015

Department of Environmental Health University of Cincinnati

Message to Students: This course is listed as Biostatistics for Public Health, but it is actually

more or less a general introduction to biostatistics and can fit to all students who may NOT be in

the major of Public Health. There is no prerequisite of statistical backgrounds to the class either.

What I hope is in the end of the class, everyone, whoever has learned statistics before or not, will

reach conclusion that she or he has learned something useful from the course. The goal of this

course has two folds: (1) I will introduce you some common but basic statistical tools such as t-

test, z-test, two sample t-test, paired t-test, ANOVA model, regression model and other non-

parametric tests; and (2) I will teach you to use SAS, THE statistical software package in the

class. I will also teach how to use Excel to handle some statistical problems. Remember, learning

statistics can be fun, especially when you start to know what to do and how to use the right tools

to solve real problems. I look forward to seeing you in my class.

Instructor: Jun Ying, PhD Department of Environmental Health University of Cincinnati Contact: Phone: 513-558-2767

Email: yingj@uc.edu Office: Kettering Lab, Room 112

Date and time: Monday 12:30-3PM Course website: NA Office hours: Appointments upon request Course Description:

Public health workers need to read and interpret public health and medical literature to keep abreast of the latest methods. This course will provide an introduction of basic concepts of statistics, methods of statistical analysis, and tools of statistical computation. The goal is to help students understand the language of statistics and the art of statistical investigation; perform basic statistical analysis of their own research; and read and evaluate analytical results in health and research articles. Course Objectives:

By the completion of this course, students will 1. Use descriptive statistics and graphical methods to describe sample data.

2. Understand the reasoning by which findings from sample data can be extended to larger, more general populations.

3. Estimate population parameters using point and interval estimation. 4. Perform hypothesis tests about one, two, or more than two population means or

proportions. 5. Use regression and correlation techniques to examine linear relationships in data. 6. Perform statistical computations and read statistical summaries using software

packages SAS Enterprise 4.3 and Excel. 7. Critically evaluate the results of scientific studies.

Content of Course:

Week Date & Day Course Material Classroom

Week 1 Jan 12 Introduction; Measures; Studies MSB E602 Week 2 Jan 19 No Class* No Week 3 Jan 26 Graphic and Summary Statistics MSB E602 Week 4 Feb 2 Probability and Distributions TBA Week 5 Feb 9 Inference, CI and HT MSB E602 Week 6 Feb 16 Inference, CI and HT MSB E602 Week 7 Feb 23 Comparing Means MSB G005G Week 8 Mar 2 Comparing Means MSB E602 Week 9 Mar 9 ANOVA MSB E602

Week 10 Mar 16 No Class** No

Week 11 Mar 23 TA or Self Review Session*** MSB E602 Week 12 April 6 Comparing Proportions MSB E602 Week 13 April 13 Comparing Proportions; Regression MSB E602 Week 14 April 20 Regression; Review MSB E602 Week 15 April 27 Final Project Due No

* Holiday: Dr. Martin Luther King Jr.'s Birthday. ** Spring Break. *** I will be in a meeting. A TA will lead the review of contents from previous chapters and address questions. Textbook and Readings:

There is NO required test book for this class. Suggested reference book for the class: Basic Biostatistics: Statistics for Public Health Practice B. Burt Gerstman, MPH, PhD, San Jose State University ISBN-13: 9780763735807 ISBN-10: 0763735809

Statistical Software: There is NO required software to purchase for this class.

However, we will learn a statistical software package called SAS Enterprise in the class. The software is installed in the classroom and available in UC libraries and many computer labs on campus. I will also teach you how to use EXCEL function in the class.

Prerequisite: There is NO prerequisite for this class.

It is expected students whoever have taken a statistical class before or not will learn statistics and its application, and computation from this class.

Criteria Included for Evaluation and Determination of Grade: 1. Homework 40% 2. In class tests 10% 3. Final Exam (Take Home Project) 45% Improvement trends will also be considered as a factor in student performance for the

determination of final grade (5%). Policy: Syllabus subject to revision as necessary.