BT2022 | COURSE MATERIALS | JAN-MAY 2023

COURSE CONTENTS

NOTE: send all the queries to rmurugan.working@gmail.com

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01 Random variable, concept of probability and probability density function, population, sample, estimates and parameters

02 Expectation operator formalism, independent and identically distributed random variables

04 Characteristic function and moments of probability density function

05 moment and cumulant generating function

07 Differential and statistical equation of normal density function

08 Standard normal deviate; Elementary convergence theorems

09 Law of large numbers (LLN)

10 Central limit theorem (CLT)

11 Student’s theory on the probable error of the sample means derived from normal populations

12 Distribution of sample means and variances derived from normal populations

13 Student theorem, Chi-square and t-distributions

14 Probable range of population mean and variance

15 Fisher F distribution on the ratio of sample variances derived from normal population

16 Statistical comparison of two different sample means or sample variances

17 Formulation of null and alternate hypothesis

18 Test of significance and confidence level

19 Type I and II errors

20 t-test, F-test and Chi-square tests

21 Multiple comparison problem

22 Concept of family wise error rate (FWER) and false discovery rate (FDR)

23 Control of FDR, Bonferroni and Benjamini procedures

24 Multidimensional statistics; bootstrap methods.

25 Correlation and regression

26 Linear and nonlinear regression of two variables

27 Multiple linear regression analysis

28 Pearson linear least square fitting procedure

29 nonlinear least square fitting using Marquardt-Levenberg algorithm

30 Design of experiments in biology

31 completely randomized design (CRD)

32 Randomized block design (RBD)

33 Development and Application of statistical workflows

34 Microarray data analysis

35 Stochastic processes, Langevin equation

36 Brownian motion

37 Fluctuation dissipation theorem

38 stochastic chemical kinetics

39 Master equations

40 Gillespie algorithm

41 Stochastic gene expression.

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