Statistics and Probability

What you’ll study

Statistics — definition and scope, nature and characteristics, population and sample, descriptive and inferential statistics, scope and applications, sources of statistical data, data collection tools, construction of questionnaires, types of data. Processing of data: measurement scales, variables and attributes, classification, array formation, tabulation, frequency distribution. Presentation of data: graphical presentation, exploratory data analysis, stem-and-leaf plots, schematic plots, five-number summaries. Characteristics of data: measures of location, dispersion, skewness and kurtosis, moments, box-and-whisker plots. Correlation analysis: bivariate data, scatter diagram, simple, rank, multiple and partial correlation. Regression analysis: regression models, estimation of parameters by OLS, polynomial and multi-variable regression. Association of attributes: independence, association and contingency tables.