Course Details
Subject {L-T-P / C} : BM4001 : Statistics for Bioengineers { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. A Thirugnanam
Syllabus
Introduction: Need of statistics for Bioengineers Variables and Scales of Measurement Types and Sources of data Organization and Classification of data (Frequency distribution) Representation of data (Tabulation, Graph and, Diagram). Probability - the basis of statistical inference, Bayes Theorem, Screening tests, sensitivity, specificity and Predictive value positive and negative. Descriptive statistics: Measures of central tendency, Measures of dispersion Probability Distributions (Binomial, Poisson, Normal) Asymmetric Distributions and Measure of shape (Skewness and Kurtosis) Inferential statistics (Hypothesis testing): Basic concepts and steps Type I and type II errors Z-tests T-test: Dependent t-test, independent t-test Chi-square test, F-test ANOVA, ANCOVA, factorial ANOVA, repeated-measures designs, mixed design ANOVA, post hoc procedures Non-parametric, distribution-free tests: Sign test, Wilcoxon signed-rank test, Wilcoxon rank sum test, Mann-Whitney U test Kruskal-Wallis H test, Friedman's test, Spearman's rank correlation test. Testing normal distribution - Kolmogorov-Smimov test Testing homogeneity of variance - Levene's test Inferential statistics (Correlation and Regression): Bivariate correlation - Pearson's correlation coefficient, Spearman's correlation coefficient Partial correlation Regression - method of least squares, assessing goodness of fit multiple regression. Experimental design and clinical trials.
Course Objectives
- To understand the fundamental statistical tools.
- To use various statistical tools for biomedical data analysis.
- To formulate a hypothesis and arrive at a statistical inference.
- Apply statistical knowledge to design and conduct research studies. <br />To estimate the value of various population parameters from a sample of data.
Course Outcomes
At the end of the course, the students will be able to: <br />1. Understand different statistical tools for biomedical data analysis. <br />2. Correctly choose and apply statistical techniques for solving problems. <br />3. Able to formulate the correct hypothesis/alternate hypothesis for the problems <br />4. Understand the power and weakness of statistics in deriving conclusion. <br />5. Apply statistical tools in experimental design and clinical trials.
Essential Reading
- • Le CT, Introductory Biostatistics, Wiley-Interscience, USA , ISBN: 0-471-41816-1
- • Wayne W Daniel, Biostatistics - Basic concepts and methodology for Health Sciences, Wiley, USA , ISBN: 978-81-265-5189-7
Supplementary Reading
- • Geller NL, Advances in clinical trial biostatistics, Marcel Dekker Inc, USA , ISBN: 0-82479032-4
- • Field A, Discovering statistics using SPSS, SAGE, USA , ISBN: 978-1-84787-936-6