Biostatistics

Data Types: Nominal, Ordinal, Interval, Ratio; Measures of Central Tendency: Mean, Median, Mode; Measures of Dispersion: Range, Variance, Standard Deviation; Application in Bioinformatics: Central tendency and dispersion in gene expression data, clinical trials, etc.

Basic Probability Theory: Conditional probability, Bayes' theorem; Probability Distributions: Normal, Binomial, Poisson, and Exponential distributions; Applications: Using probability distributions in modeling biological events (e.g., mutation rates, genetic inheritance patterns).

Hypothesis Testing Basics: Null and Alternative Hypothesis, Type I and Type II errors, p-value interpretation; Tests: t-tests (one-sample, independent two sample, paired), Chi-square test, One- Way and Two-Way ANOVA; Applications: Testing differences in gene expression between treatments, patient groups, or populations.

Regression Analysis: Simple linear regression, Multiple regression; Survival Analysis: Kaplan-Meier curves, Cox Proportional-Hazards model; Multivariate Analysis: Principal Component Analysis (PCA), Cluster Analysis; Applications: Gene expression predictions using regression, survival analysis in clinical trials, and clustering genes with similar expression patterns. Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh

Statistical Software: Introduction to R, SPSS, and Python for bioinformatics data analysis; Data Visualization: Creating effective plots (histograms, box plots, scatter plots) and interpreting results; Application: Visualizing and interpreting gene expression data, clinical trial results.