Overview of Biostatistics - Basic Concepts, Distributions, Estimation, Hypothesis Testing, Regression, Clinical Trials, and Beyond
This overview covers fundamental statistical concepts, from measures of location and variation to exploring various types of data. It delves into important distributions like the Normal distribution, along with estimation techniques, hypothesis testing methods, regression analysis, design of experiments, sample size calculations, time-to-event analysis, and statistics in clinical trials. The content provides a comprehensive look at the field of biostatistics and its applications in research and clinical settings.
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Presentation Transcript
Overall agenda Part 1 and 2 Part 1: Basic statistical concepts and descriptive statistics summarizing and visualising data describing data - measures of location and variation - exploring data - types of data population and sample Part 2: Statistical Distributions concepts important distributions: - Normal distribution and related - other important continuous distributions (life-time and survival distributions) - discrete distributions (binomial, Poisson, count data) 1 | Introduction to Biostatistics | Ekkehard Glimm | 9/10 December 2013 | Part 1
Overall agenda Part 3 and 4 Part 3: Estimation and confidence intervals point estimates interval estimates point and interval estimates for various types of data prediction intervals Part 4: Hypothesis testing Concept important statistical tests: - t-tests (one/paired sample, two sample with and without equal variances) - F-tests and ANOVA - testing parameters in more general models - testing hypotheses about count and binomial data 2 | Introduction to Biostatistics | Ekkehard Glimm | 9/10 December 2013 | Part 1
Overall agenda Part 5 and 6 Part 5: Regression and correlation method of least squares and simple linear regression Multiple linear regression correlation extensions: ANOVA as regression; logistic, Poisson and non-linear regression Part 6: design of experiments and sample size calculations types of experiments: clinical trials, observational studies, other planned experiments (parallel group designs and cross-over designs, factorial experiments) principles of experimentation: blinding, randomization, stratification operating characteristics and sample size assessment 3 | Introduction to Biostatistics | Ekkehard Glimm | 9/10 December 2013 | Part 1
Overall agenda Part 7 and 8 Part 7: time-to-event analysis why this is special and important: survival times and censoring Kaplan-Meier curve hazard ratio the log-rank test extensions: Cox regression Part 8: Statistics in clinical trials phases of Clinical Development: - pre-clinical research and transition Preclinical-Clinical - clinical Development Phase I - clinical development: Phases II-IV describing statistical methods and reporting statistical results 4 | Introduction to Biostatistics | Ekkehard Glimm | 9/10 December 2013 | Part 1
