Probability and Statistics for Data Science

Introduction to Data Science Data Science Life Cycle Descriptive and Inferential Statistics Measures of central tendency Measures of dispersion

Skewness and Kurtosis Moments Introduction and definition of Probability Event and Sample Space Law of addition and multiplication of Probabilities Conditional Probability Independent and Dependent events Bayes theorem Mathematical Expectations Moment generating functions

Discrete Distribution Binomial and Poisson Distribution Continuous Distribution Rectangular and Normal distribution Curve fitting Methods of Least square fitting a Straight line and a Parabola

Correlation Coefficient of Correlation Rank Correlation Lines of Regression Multiple and Partial Correlation

Null and Alternative hypothesis two types of errors level of significance and power of the test Chi-square distribution test of popular variance test of goodness of fit t F Z distribution