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Probability and Statistics (3130006)

Teaching Scheme (in Hours)

Theory Tutorial Practical Total
3 2 0 5

Subject Credit :  5

Examination Scheme (in marks)

PA (M)
ESE Viva (V)
PA (I)
70 30 0 0 100

Syllabus Content    Download

Unit-1:  Basic Probability

Experiment, definition of probability, conditional probability, independent events, Bayes' rule, Bernoulli trials, Random variables, discrete random variable, probability mass function, continuous random variable, probability density function, cumulative distribution function, properties of cumulative distribution function, Two dimensional random variables and their distribution functions, Marginal probability function, Independent random variables.

Unit-2:  Some special Probability Distributions

Binomial distribution, Poisson distribution, Poisson approximation to the binomial distribution, Normal, Exponential and Gamma densities, Evaluation of statistical parameters for these distributions

Unit-3:  Basic Statistics

Measure of central tendency: Moments, Expectation, dispersion, skewness, kurtosis, expected value of two dimensional random variable, Linear Correlation, correlation coefficient, rank correlation coefficient, Regression, Bounds on probability, Chebyshev‘s Inequality

Unit-4:  Applied Statistics

Formation of Hypothesis, Test of significance: Large sample test for single proportion, Difference of proportions, Single mean, Difference of means, and Difference of standard deviations. Test of significance for Small samples: t- Test for single mean, difference of means, t-test for correlation coefficients, F- test for ratio of variances, Chi-square test for goodness of fit and independence of attributes.

Unit-5:  Curve fitting by the numerical method

Curve fitting by of method of least squares, fitting of straight lines, second degree parabola and more general curves

Course Outcome

  • Understand the terminologies of basic probability, two types of random variables and their probability functions
  • Observe and analyze the behavior of various discrete and continuous probability distributions
  • Understand the central tendency, correlation and correlation coefficient and also regression
  • Apply the statistics for testing the significance of the given large and small sample data by using t- test, F- test and Chi-square test
  • Understand the fitting of various curves by method of least square

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