Complex numbers system and complex variable theory: Introduction to complex number systems. De Moiver’s theorem and its applications. Complex functions, Cauchy-Riemann equations (in Cartesian and polar coordinates). Complex integration, singularities, poles, residues, and contour integration and applications.
Data organization: Frequency distribution and geometrical representation of data..
Descriptive measures: Measures of central tendency, measures of dispersions.
Simple Regression and Correlation: Regression analysis by least squares method, testing the significance of the slope; simple correlation analysis, coefficient of correlation, and coefficient of determination, testing the significance of r. Rank correlation.
Probability: Introduction to probability, counting techniques, dependent and independent events, conditional probability, additive rule of probability, and its applications. Contingency tables, joint and marginal probabilities, the multiplication rule, and Baye’s theorem.
Probability Distribution: Concept of random variable, discrete probability distribution. Case study. Continuous probability distribution with examples, Probability destiny function, joint probability distribution, Examples. Mean of a random variable. Variance of a random variable. Binomial distribution. Mean and variance of binomial distribution. Examples. Poisson distribution, Normal distribution, area under the normal curve. Standard normal distribution, inverse use of table of areas under the normal curve.
