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UNIT-I
1) Introduction to Statistics:
a. Certain impossible and random events,
b. Random variable expected value and its variance
c. Probability distribution of random variable
d. Conditional probability and its most elementary basic formulae
e. Bayes' theorem and its applications
f. Computation of posterior Probability
g. Discrete Uniform distribution: concept, properties and its applications
h. Bernoulli trials, the law of large numbers
2) Binomial and Poisson distributions:
a. Definition of Binomial and Poisson distributions
b. Their properties and applications.
c. Fitting of Binomial and Poisson distribution
3) Normal distribution:
a. Definition of Normal distribution
b. Standard Normal Distribution and its properties
c. Numerical problems on Normal distribution.
4) Exponential and Gamma probability distributions:
a. Definition of Exponential and Gamma probability distributions. and its properties
5) Genetical statistics:
a. Random mating populations
b. Sex linked characters
c. Selection
d. Hardy-Weinberg Law.
e. Introduction to Poisson process
6) Markov chain:
a. Definition
b. Transition probability matrix,
c. Steady states
d. Transient chains
e. Periodic chains
7) Random walk models:
a. Random walk models
b. Sensitivity and specificity
UNIT-II
1) Chi-square test:
a. Chi-square test
b. Testing heterogeneity and homogeneity
c. Detection and estimation of linkage
d. Linkage ratios and its estimation,
e. Use in genetic experiment
f. Estimation of component of variation due to interaction between G x E (genotypic x environment) and its significance.
2) Analysis of variance:
a. One-way analysis
b. Two-way classification
c. Analysis of covariance with one auxiliary character
d. Concept of incomplete block designs
