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AKTU Biostatistics (BBI064) Syllabus PDF – B.Tech 3rd Year
Biostatistics BBI064
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Official AKTU syllabus of Biostatistics (BBI064) for B.Tech 3rd Year – 3 credits, L-T-P 3-0-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Biostatistics
Download PDFBBI064 · 3 credits · L-T-P 3-0-0
Course Outcomes
At the end of the course, the student will be able to:
| CO1 | Explain fundamental statistical concepts including data types, central tendency, and dispersion. | K2 |
| CO2 | Apply probability theory and probability distributions to model biological events. | K3 |
| CO3 | Apply statistical inference and hypothesis testing to biological data. | K3 |
| CO4 | Apply regression, survival analysis, and multivariate techniques to biological datasets. | K3 |
| CO5 | Use statistical software and data visualization tools to interpret biological data. | K3 |
Course Content
L-T-P: 3-1-0
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | FUNDAMENTAL STATISTICAL CONCEPTS: 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. | 08 |
| II | PROBABILITY AND PROBABILITY DISTRIBUTIONS: 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). | 08 |
| III | STATISTICAL INFERENCE AND HYPOTHESIS TESTING: 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. | 08 |
| IV | ADVANCED DATA ANALYSIS TECHNIQUES: 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. | 08 |
| V | STATISTICAL SOFTWARE AND DATA VISUALIZATION: 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. | 08 |
Text Books
- Wayne W. Daniel, Chad L. Cross, “Biostatistics: A Foundation for Analysis in the Health Sciences”, 10th edition, Wiley, 2013.
- S. N. Gupta, “Fundamentals of Biostatistics”, 5th edition, Himalaya Publishing House, 2015.
- Dr. B. K. Mahajan, “Biostatistics and Research Methodology”, 1st edition, Jaypee Brothers Medical Publishers, 2016.
- Dr. S. K. Srivastava, A. Bhardwaj, “Biostatistics – A Practical Approach”, 1st edition, Global Vision Publishing House, 2010.
- Marcello Pagano, Kimberlee Gauvreau, “Principles of Biostatistics”, 2nd edition, Brooks/Cole, 2000.
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