Osmania University Hyderabad Bsc

Can you please give here the syllabus of the BSC statistics course of the Osmania University Hyderabad as I am looking for the same ?

[Quick Sam]

As you want I am here giving you the syllabus of the BSC statistics course of the Osmania University Hyderabad.

Syllabus :

Paper-I : Descriptive Statistics and Probability Distributions

Unit –I
Descriptive Statistics: Concept of primary and secondary data. Methods of collection and editing of
primary data. Designing a questionnaire and a schedule. Sources and editing of secondary data.
Classification and tabulation of data. Measures of central tendency (mean, median, mode, geometric
mean and harmonic mean) with simple applications. Absolute and relative measures of dispersion
(range, quartile deviation, mean deviation and standard deviation) with simple applications.
Importance of moments, central and non-central moments, and their interrelationships, Sheppard’s
corrections for moments for grouped data. Measures of skewness based on quartiles and moments
and kurtosis based on moments with real life examples.

Probability: Basic concepts in probability—deterministic and random experiments, trail, outcome,
sample space, event, and operations of events, mutually exclusive and exhaustive events, and equally
likely and favourable outcomes with examples. Mathematical, statistical and axiomatic definitions
of probability with merits and demerits. Properties of probability based on axiomatic definition.
Conditional probability and independence of events. Addition and multiplication theorems for n
events. Boole’s inequality and Bayes’ theorem. Problems on probability using counting methods
and theorems.

UNIT-II
Random Variables: Definition of random variable, discrete and continuous random variables,
functions of random variables, probability mass function and probability density function with
illustrations. Distribution function and its properties. Transformation of one-dimensional
random variable (simple 1-1 functions only). Notion of bivariate random variable, bivariate
distribution and statement of its properties. Joint, marginal and conditional distributions.
Independence of random variables.

Mathematical Expectation: Mathematical expectation of a function of a random variable. Raw
and central moments and covariance using mathematical expectation with examples.
Addition and multiplication theorems of expectation. Definition of moment generating function
(m.g.f), cumulant generating function (c.g.f), probability generating function (p.g.f) and
characteristic function (c.f) and statements of their properties with applications. Chebyshev’s ,
and Cauchy-Schwartz’s inequalities and their applications
syllabus of the BSC statistics course





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