Page 9 - MTech-Medical Nanotechnology
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SASTRA Deemed to be University                                                  M. Tech. (Medical Nanotechnology)
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                    Course Code: MAT544                                                    3   1   0   4
                    Semester: I

                                      BIOSTATISTICS AND DESIGN OF EXPERIMENTS

                    Course objective:
                    The course aims to equip students with the basic concepts of statistics, data analysis, data
                    interpretation and statistical experimental design.

                    UNIT- I                                                                       15 Periods
                    INFERENTIAL STATISTICS AND ONE SAMPLE HYPOTHESIS TESTING
                    Samples and populations: Random, stratified and cluster sampling; Single- and Double-blind
                    experiments;  Point  and  interval  estimates;  Sampling  distributions:  t,  chi-square,  F
                    distributions;  Hypothesis  testing:  null  and  alternative  hypotheses,  decision  criteria,  critical
                    values, type  I  and  type  II  errors,  Meaning of statistical significance;  Power  of  a test;  One
                    sample  hypothesis  testing:  Normally  distributed  data:  z,  t  and  chi-square  tests;  Binomial
                    proportion testing.

                    UNIT - II                                                                     15 Periods
                    MULTI-SAMPLE AND NONPARAMETRIC HYPOTHESIS TESTING
                    Two sample hypothesis testing; Nonparametric methods: signed rank test, rank sum test;
                    Kruskal-Wallis test; Analysis of variance: One-way ANOVA.

                    UNIT - III                                                                    15 Periods
                    CURVE FITTING
                    Regression  and  correlation:  simple  linear  regression;  Least  squares  method;  Analysis  of
                    enzyme kinetic data; Michaelis-Menten; Line weaver-Burk and the direct linear plot; Logistic
                    Regression; Polynomial curve fitting.

                    UNIT - IV                                                                     15 Periods
                    DESIGN OF EXPERIMENTS
                    Single factor experiments; Randomized block design; Plackett-Burman Design; Comparison
                    of  k  treatment  means;  Factorial  designs;  Blocking  and  confounding;  Response  surface
                    methodology.

                    REFERENCES
                    1.  J. H. Zar, Biostatistical Analysis, 5/e, Pearson, 2014.
                    2.  E. Kreyszig, Advanced Engineering Mathematics, 10/e, John Wiley, 2015.
                    3.  D. C. Montgomery, Design and Analysis of Experiments, 8/e, Wiley, 2013.








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