Statistical Concepts and Terminology: Population, sample, nominal, ordinal, continuous data

Statistical Measures and Descriptive Statistics: Central tendency (average or mean, median, mode), dispersion measures such as range, variance, standard deviation, coefficient of variation, unbiased estimates

Graphical Techniques: Histograms, bar charts, box plots.

Distributions: Normal, t-distribution, skewed distributions

Inferential Statistics: Point and interval estimates of the mean and variance of a population.  Hypothesis testing for the mean and variance of a population.

Risk Assessment: Relative risk, odds ratio, Bayes risk.

DAY TWO

Defining a Sound Scientific Study: Selection criteria to statistical considerations

Single Therapy Protocols: Phase I and Phase II clinical trials, sample size and analyses, simple regression techniques

Comparative Studies: Defining appropriate study hypotheses, study objectives, defining efficacy measures and endpoints (response), sample size considerations, quantitative measures, analyses (continuous and discrete data), case control studies

Data Presentation:  Interpretation and discussion of results from actual clinical data computer output for categorical and continuous endpoints, p-values, statistical significance, risk measures.

DAY THREE

Multiple Treatment Studies:  Analysis of Variance (ANOVA), multiple regression

Multiple Treatment Clinical Protocols:  Phase III protocol sample size and comparative analyses (response and survival techniques)

Equivalence and Non-Inferiority Studies: Point and interval testing for equivalence,
Non-inferiority and superiority graphical techniques

Meta-Analytic Techniques: Presentation of individual patient vs. literature based meta-analyses, statistical tests of homogeneity and pooled effect size


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