01
Basic Probability
Probability spaces, conditional probability, independence, discrete random variables, multinomial distribution, Bernoulli trials, expectation, moments, variance, correlation coefficient and Chebyshev's Inequality.
Complete unit-wise study material for AL302 Introduction to Probability and Statistics for RGPV Artificial Intelligence and Machine Learning III Semester students.
The objective of this course is to familiarize students with statistical techniques. It aims to equip students with standard concepts and tools at an intermediate to advanced level that will help them tackle various problems in the discipline.
The AL302 syllabus contains six units covering probability, probability distributions, statistics and statistical testing.
Probability spaces, conditional probability, independence, discrete random variables, multinomial distribution, Bernoulli trials, expectation, moments, variance, correlation coefficient and Chebyshev's Inequality.
Continuous random variables and their properties, distribution functions and densities, normal distribution, exponential distribution and gamma densities.
Bivariate distributions and their properties, distribution of sums and quotients, conditional densities and Bayes' rule.
Measures of central tendency, moments, skewness, kurtosis, Binomial, Poisson and Normal distributions, correlation, regression and rank correlation.
Curve fitting using least squares, straight lines, second degree parabolas, general curves and large sample tests of significance.
Tests for single mean, difference of means, correlation coefficients, ratio of variances, Chi-square goodness of fit and independence of attributes.
Complete unit-wise syllabus for RGPV Artificial Intelligence and Machine Learning III Semester.
Probability spaces, conditional probability, independence; discrete random variables, independent random variables, the multinomial distribution, Poisson approximation to the binomial distribution, infinite sequences of Bernoulli trials, sums of independent random variables; expectation of discrete random variables, moments, variance of a sum, correlation coefficient and Chebyshev's Inequality.
Continuous random variables and their properties, distribution functions and densities, normal, exponential and gamma densities.
Bivariate distributions and their properties, distribution of sums and quotients, conditional densities and Bayes' rule.
Measures of central tendency: moments, skewness and kurtosis. Probability distributions: Binomial, Poisson and Normal. Evaluation of statistical parameters for these three distributions, correlation and regression and rank correlation.
Curve fitting by the method of least squares, fitting of straight lines, second degree parabolas and more general curves. Test of significance: large sample test for single proportion, difference of proportions, single mean, difference of means and difference of standard deviations.
Test for single mean, difference of means and correlation coefficients, test for ratio of variances, Chi-square test for goodness of fit and independence of attributes.
AL302 Introduction to Probability and Statistics provides the mathematical and statistical foundation needed to understand probability models, random variables, distributions and statistical analysis.
Students can use this page to access all six units of AL302 in one place and prepare unit-wise according to the RGPV syllabus.
Select any unit and start your Probability and Statistics preparation.
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