Biostatistics and Bioinformatics

Biography

Biography: Abdel-Salam Gomaa

Abstract

This short course is designed to provide some of the advanced and common statistical techniques for researches and practitioners. The short course will demonstrate the parametric simple and multiple linear regression models, Logistic Regression, Poisson Regression, ZIP Poisson Regression models and their applications in Biostatistics, Medical, Biology, Business, Mass Communication, Engineering, public health, Epidemiology, pharmaceutical and biomedical fields. These examples and case-studies will be implemented using the SPSS and SAS.  Attendees will learn concepts, techniques and some secrets about the followings: How to use the F-test to determine if your predictor variables have a statistically significant relationship with your outcome/response variable? What are the assumptions for linear regression analysis and what you should do to meet these assumptions? Why adjusted R2 is smaller than R2 and what these numbers mean when comparing between several models? For which predictors are the regression coefficients significantly different than zero and how can you select the significant variables? What is the difference between regression and ANOVA and when are they equivalent? When and how to use the Generalized Linear Models with some examples? How to select the best model? What is the general strategy to approach any modeling problem? How to report the results in your research paper/report?