This course is meant for students who do not have sufficient background of Statistical Methods. The students would be exposed to concepts of statistical methods and statistical inference that would help them in understanding the importance of statistics. It would also help them in understanding the concepts involved in data presentation, analysis and interpretation. The students would get an exposure to presentation of data, probability distributions, parameter estimation, tests of significance, regression and multivariate analytical techniques.
- Descriptive statistics: Exploratory data analysis techniques. Random variable.
- Discrete probability distributions: Uniform, Bernoulli, Binomial, Poisson, Negative - binomial, Geometric, Hypergeometric, Multinomial. Continuous probability distributions: Rectangular, Exponential, Cauchy, Normal, Gamma, Beta, Weibull, Lognormal, Logistic, Pareto.
- Exact sampling distributions. Central t, χ2 and F distributions. Bivariate normal distribution - conditional and marginal.
- Correlation, Rank correlation, Correlation ratio, Intra-class correlation. Regression analysis, Partial and multiple correlation and regression.
Fitting of discrete distributions and test for goodness of fit. Fitting of continuous distributions and test for goodness of fit. Computation of simple, multiple and partial correlation coefficient. Correlation ratio and intra-class correlation. Regression coefficients and regression equations. Fitting of Pearsonian curves. Analysis of association between attributes, categorical data.