Understanding Clinical Research: Behind the Statistics

This module provides an introduction to different study types in clinical research, including observational, experimental, case series, case-control, cross-sectional, and cohort studies. Learners will gain a solid understanding of the various study designs and their applications in research.

This module focuses on data description, covering key concepts, data types, measures of central tendency, measures of dispersion, and sampling methods. Learners will also explore descriptive statistics and visual representation of data.

In this module, learners will build an intuitive understanding of statistical analysis, including concepts such as P-values, probability, distributions, central limit theorem, and more. Practical examples and case studies will enhance comprehension of statistical concepts.

This module delves into hypothesis testing and confidence intervals. Learners will explore null and alternative hypotheses, hypothesis testing errors, confidence levels, and interval estimation. Practical exercises and self-assessment quizzes are included to reinforce learning.

Learners will explore parametric and nonparametric tests in this module, including the use of Student's t-test, ANOVA, linear regression, and nonparametric tests for comparing data. Practical applications and case studies will reinforce understanding of test selection.

This module focuses on analyzing categorical data, covering contingency tables, chi-square tests, Fisher's exact test, sensitivity and specificity, predictive values, and risk and odds ratios. Learners will gain practical skills in analyzing accuracy of results for categorical data.