Introductory probability and descriptive statistics for data analysis and research.
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.
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.
Probability distribution function, Joint probability distribution of two random variables, Discrete distributions: Bernoulli trial, Binomial and Poisson distributions.
Bivariate data, Bivariate frequency distribution, Correlation between two variables, Karl Pearson's coefficient of correlation(r), Spearman's rank correlation.
