Biostatistics * : Courses

STA 111 Introduction to Probability and Statistics I

Credits: 1
Semester(s): Fall, Spring
Type: REC
Grading: Graded (A-F)
Designed especially for students in the humanities or the social sciences. Focuses primarily on the fundamental ideas of probability, and introduces statistics.

STA 112 Introduction to Probability and Statistics II

Credits: 3
Semester(s): Spring
Type: LEC
Grading: Graded (A-F)
Recommended for undergraduate students in the health sciences. Covers basic statistical concepts and techniques such as descriptive statistics, regression and correlation, analysis-of-variance, survival analysis and categorical data analysis as it pertains to clinical experiments and epidemiological investigations.

STA 119 Statistical Methods

Credits: 1
Semester(s): Fall, Spring
Co-requisite: Students must enroll in LEC and REC in the same term
Type: REC
Grading: Graded (A-F)
Covers topics in descriptive statistics, probability, inference, and experimental design, all of which are put together to draw conclusions from uncertainty through analysis of experimental data. Although a general statistical methods course, the material (through examples) is geared towards sciences majors, especially those in the health sciences. Looks into the underlying reasoning behind the techniques rather than just pure application.

STA 301 Intro to Probability

Credits: 3
Semester(s): (No information on typically offered semesters)
Co-requisite: Students must enroll in LEC and REC in the same term.
Type: LEC
Grading: Graded (A-F)

STA 302 Intro Stat Inference

Credits: 3
Semester(s): (No information on typically offered semesters)
Pre-requisites: STA 301 Or MTH 411
Co-requisite: Student must register for LEC And REC in the same term
Type: LEC
Grading: Graded (A-F)

STA 403 Regression Analysis

Credits: 3
Semester(s): (No information on typically offered semesters)
Type: LEC
Grading: Graded (A-F)
Covers regression analysis and introduction to linear models. Topics include multiple regression, analysis of covariance, least square means, logistic regression, and non-linear regression. The course includes a one-hour computer lab and emphasizes hands-on applications to datasets from the health sciences.

STA 404 Stat Compar & Assoc

Credits: 3
Semester(s): (No information on typically offered semesters)
Pre-requisite: STA 403 Or Permission of Instructor
Type: LEC
Grading: Graded (A-F)
Advanced presentation of statistical methods for comparing populations and estimating and testing associations between variables. Topics include point estimation; confidence intervals; hypothesis testing; ANOVA models for 1, 2, and k way classifications; multiple comparisons; chi-square test of homogeneity; Fisher's exact test; McNemar's test; measures of association, including odds ratio, relative risks, Mantel-Haenszel tests of association, and standardized rates; repeated measures ANOVA; simple regression; and correlation.

STA 406 Introduction to Statistical Computing

Credits: 3
Semester(s): (No information on typically offered semesters)
Pre-requisite: STA 119 or permission of instructor
Type: LEC
Grading: Graded (A-F)
The purpose of this course is to familiarize students with PC-based statistical computing applications for public health This course will develop basic skills in the use of a statistical package through classroom demonstrations and independent lab assignments. Te course will emphasize data definition, verification, descriptive and inferential statistics, and graphical presentation. The course should familiarize the students with the use of a statistical package and give them the skills needed for effective data management, data manipulation, and data analysis at a basic level.

STA 427 Introduction to Medical Statistics

Credits: 3
Semester(s): Spring
Co-requisite: Students need to enroll in REC and LEC in the same term.
Type: LEC
Grading: Graded (A-F)
Topics include descriptive statistics, probability concepts (such as independence and conditional probability), probability distributions of random variables, sampling distributions, estimation, confidence intervals, hypothesis testing, analysis of variance procedures, linear regression, and nonparametric methods. Computers and statistical packages are used throughout the course. Requires no extensive computer experience.

Updated: 13 Nov 2012 06:02:26 EST