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Biostatistics I : Florin Vaida, Ph.D.

Objectives: the students will develop and acquire the insight, tools and skills needed to be educated users and consumers of biostatistics.  They will recognize data types, and correctly identify the statistical methods appropriate for analysis of a given clinical dataset.  They will understand the basic concepts of statistics, including elementary probability theory, sampling, estimation, confidence intervals, and hypothesis testing.  They will be able to conduct graphical and numerical exploratory data analysis using SPSS, and to perform statistical analyses, including comparative tests of categorical and continuous data.

Course Content

Topic Content

Data summaries          

Numeric and graphic data summaries in SPSS

Probability and normal distribution

Elementary probability theory; the normal distribution

Central limit theorem and confidence intervals

Sampling distributions and applications to statistical inference

Hypothesis testing for one group

Hypothesis testing: type I and II error, 1-sided and 2-sided tests; t-test for one group

Statistical inference for two groups

Paired and independent groups t-test; Wilcoxon rank-sum test; sample size calculation

Inference for proportions

Binomial distribution; one-sample z-test for proportions; McNemar’s test for paired samples

Inference for proportions, two groups

Comparing proportions in independent groups: z-test, Chi-square test, Fisher’s exact test. 

One-way ANOVA

One-way analysis of variance; F-test; adjusting for multiple post-hoc comparisons 

Two-way ANOVA


Additive and factorial two-way ANOVA; model selection 

2020 Syllabus