Probability and Statistics

Contents: Statistics & Role of Statistics in Decision Making. Branches of Statistics. Fundamental elements of Statistics. Variables and their types, Data and its sources, Scales of measurements. Tabulation and classification of data. Graphs and Charts: Stem-and leaf diagram, Box and Whisker plots and their interpretation. Measures of Central Tendency, Quantiles. Measures of Dispersion: Their properties, usage, limitations and comparison. Moments, Measures of Skewness and Kurtosis and Distribution shapes. Rates and ratios, Standardized scores and their interpretation. Probability Concepts, Addition and Multiplication rules. Joint and marginal probabilities, Conditional probability and independence. Random Variable, difference between discrete and continuous random variable, Expected value of Random Variable. Discrete Probability Distributions: Binomial Distribution, Poisson Distribution. Continuous Probability Distributions: Normal and Application of the Normal Distribution. Practice question of Normal distribution. Introduction to hypotheses testing and regression analysis. Use of SPSS/R and MS-excel For calculation of descriptive summary and graphical presentation of the data.