Unit 1

Lectures 6

Introduction to Biostatistics-Need for Biostatistical Methods –Their uses and Misuses, Types of Variables, Data collection Methods, Population and Sample.

Descriptive Data Analysis Methods- Statistical Tables, Diagrams examples; Graphs, Measures of Central Tendencies and Dispersion, Correlation Analysis Methods, Linear Regression Analysis.

Unit 2

Lectures 6

Theory of probability, Standard Probability Distributions – Discrete distributions Binomial and Poisson;, Univariate continuous distribution – Normal, and standard normal.

Unit 3

Lectures 6

Tests of Significance of Statistical Hypotheses- Concept of Hypotheses –Null and Alternative hypotheses, Type I and Type II errors, Significance level, Critical region, Power of a test , P- value and its interpretation; Large and Small Sample Test – Normal test, Student’s ‘t’ test, Chi-square tests, Analysis of variance.

Unit 4

Lectures 6

Nonparametric methods-Non-parametric methods for estimation, Methods for tests of significance for the independent and correlated samples, Nonparametric Methods for more than two populations..

Prerequisite: Undergraduate level statistics and biology

Total number of classes: 30

Statistical Data Analysis is a course offered in the first semester of the program M. Sc. Molecular Medicine (MLM) at Amrita Vishwa Vidyapeetham.

Evaluation Pattern: 50+50 = 100

Textbooks

• Statistical Techniques for data Analysis: J.K. Taylor & Cheryl C, 2004 Chapman & Hall (CRC).
• Performing Data Analysis Using IBM SPSS: Lawrence S Meyers, 2015, John Wiley..

Reference

• Biostatistics: A Foundation for Analysis in the Health Sciences: Daniel, Wayne W 8^thEd. 2005.