Statistics I

Basic concept of statistics; Application of Statistics in the field of Computer Science & Information technology; Scales of measurement; Variables; Types of Data; Notion of a statistical population

Measures of central tendency; Measures of dispersion; Measures of skewness; Measures of kurtosis; Moments; Steam and leaf display; five number summary; box plot Problems and illustrative examples related to computer Science and IT

Concepts of probability; Definitions of probability; Laws of probability; Bayes theorem; prior and posterior probabilities Problems and illustrative examples related to computer Science and IT

Definitions of population; sample survey vs. census survey; sampling error and non sampling error; Types of sampling 5. Random Variables and Mathematical Expectation (5 Hrs.) Concept of a random variable; Types of random variables; Probability distribution of a random variable; Mathematical expectation of a random variable; Addition and multiplicative theorems of expectation Problems and illustrative examples related to computer Science and IT\n21

Probability distribution function, Joint probability distribution of two random variables; Discrete distributions: Bernoulli trial, Binomial and Poisson distributions; Continuous distribution: Normal distributions; Standardization of normal distribution; Normal distribution as an approximation of Binomial and Poisson distribution; Exponential, Gamma distribution Problems and illustrative examples related to computer Science and IT

Bivariate data; Bivariate frequency distribution; Correlation between two variables; Karl Pearson’s coefficient of correlation(r); Spearman’s rank correlation; Regression Analysis: Fitting of lines of regression by the least squares method; coefficient of determination Problems and illustrative examples related to computer Science and IT