STATISTICAL ASSISTANT IN KERALA STATE INDUSTRIAL
DEVELOPMENT CORPORATION LIMITED
(CATEGORY NO. 208/2010)
syllubus
1. Collection, Classification and Diagrammatic representation of data:
Measures of central tendency and measures of deviation, Correlation and
Regression, Partial and Multiple correlation.
2. Basic probability theory: Definitions, Addition theorem, Multiplication
theorem, Conditional probability and Baye’s theorem. Theorem of total
probability – Random variables-expectation, moments, generating
functions-sequences of random variables and independence of random
variables. Law of large numbers, Central limit theorem and its
applications.
3. Distribution theory (i) Discrete distributons – Binomial, Poisson, Negative
– binomial, Geometric, Hyper-geometric and Multinomial distributions.
(ii) Continuous distributions-Uniform, Exponential, Gamma, Beta,
Normal, Log-normal, Logistic, Weibull, Pareto and bivariate normal,
distributions
(iii) Sampling distributions: Student’s t, F and Chi-square distributions.
4. (i) Estimation: Basic properties of estimators, concepts of sufficiency,
UMVUE and completeness, Methods of estimation.
(ii) Tests of Hypotheses – Two types of errors , significance level, size and
power of a test, Tests based on normal, t, Chi-square and F distributions.
