 inear regression linear regression is the simplest form of statistical modeling for modeling the relationship between response dependent variable and one or more independent variables such that the response variable typically follows normal distribution the statsmodels regression module allows us to learn linear models on data with iid independently and identically distributed errors this module allows us to use different methods like ordinary least squares (ols)weighted least squares (wls)generalized least squares (gls)and so onfor the estimation of the linear model parameters  eneralized linear models normal linear regression can be generalized if the dependent variable follows different distribution than the normal distribution the statsmodels genmod module allows us to extend the normal linear models to different response variables this allows us to predict the linear relationship between the independent and dependent variable when the dependent variable follows distributions other than normal distributions anova analysis of variance is process of statistical processes used to analyze the difference between group means and associated procedures anova analysis is an important way to test whether the means of several groups are equal or unequal this is an extremely powerful tool in hypothesis testing and statistical inference and is implemented in the anova_lm module of the statsmodel package time series analysis time series analysis is an important part of data analytics lot of data sources like stock pricesrainfallpopulation statisticsetc are periodic in nature time series analysis is used find structurestrendsand patterns in these streams of data these trends can be used to understand the underlying phenomena using mathematical model and even make predictions and forecasts about future events basic time series models include univariate autoregressive models (ar)vector autoregressive models (var)univariate autoregressive moving average models (arma)as well as the very popular autoregressive integrated moving average (arimamodel the tsa module of the statsmodels package provides implementation of time series models and also provides tools for time series data manipulation statistical inference an important part of traditional statistical inference is the process of hypothesis testing statistical hypothesis is an assumption about population parameter hypothesis testing is the formal process of accepting or rejecting the assumption made about the data on the basis of observational data collected from samples taken from the population the stats stattools module of statsmodels package implements the most important of the hypothesis tests some of these tests are independent of any modelwhile some are tied to particular model only nonparametric methods nonparametric statistics refers to statistics that is not based on any parameterized family of probability distributions when we make an assumption about the distribution of random variable we assign the number of parameters required to ascertain its behavior for exampleif we say that some metric of interest follows normal distribution it means that we can understand its behavior if we are able to determine