This course covers topics in statistical analysis at a professional-level is designed to assist the future health leader in understanding and interpreting data and in the role of decision maker. The course covers the collection, aggregation, and presentation of data and basic descriptive and inferential statistics. Doctoral students will get hands-on application of spreadsheets and statistical software to the solution of various statistics problems. Statistical software package: WINKS 7 SDA
- Critical consumers of the public health and medical literature by understanding the basic principles and methods of epidemiology, including disease (outcome) measures, measures of association, study design options, bias, confounding, and effect modification.
- Able to design valid and efficient studies to address public health and clinical problems.
- Able to organize, summarize, and display quantitative data.
- Comfortable with statistical methods for calculating summary estimates, measures of variability, and confidence intervals.
- Able to carry out and interpret a variety of tests of significance, including correlational matrix analysis, two-group comparisons using t-tests, paired t-test, 2-way ANOVA, ANCOVA, Repeated Measures ANOVA, Multiple Logistic Regression, Time-Series Analysis, etc.
- Familiar with power and sample size calculations.
- Able to carry out simple data analyses using the WINKS 7 SDA program.