Syllabus: 

1. Regression Analysis - I

   • • Building a regression model: Transformations – Box-Cox and Box-Tidwell models, Stepwise regression, Model selection (adjusted R2, cross validation and Cp criteria, AIC, PRESS).

     • Multicollinearity – detection and remedial measures. Dummy variables, piecewise regression, splines and scatter plot smoothing. 

     • Detection of outliers and influential observations: residuals and leverages, DFBETA, DFFIT, Cook’s Distance and COVRATIO. 

     • Checking for normality: Q-Q plots, Normal Probability plot, Shapiro-Wilks test. 

     • Departures from the Gauss-Markov set-up: Heteroscedasticity and Autocorrelation – detection and remedies.

2. Regression Analysis - II

   • • Measures of association for classified nominal and ordinal categorical data. 

     • Generalized Linear Models: Introduction, Components of a GLM, Maximum Likelihood estimation, Deviance. 

     • Binary data and Count data: ungrouped and grouped. Models with constant coefficient of variation. Polytomous data. Overdispersion and fitting by quasi-likelihood. 

     • Extensions of GLMs: Zero inflated Poisson models, Joint modelling of mean and variance, Concept of Generalized Additive Models (GAM).

Guide: Saikat Kar (Feel free to connect)

Duration: 2.5 months (18 classes)

Time: 7:00 PM - 9:00 PM IST (Preferable)

Fees: INR 1250 INR 125 - 200 per hour* 

Registration Link: click here 

Note:

• Course is customizable in certain extent

• *Fees is negotiable based on batch size. Conditions applied.

• 75% Attendance is mandatory for all. Who will not attend he/she need to check the recording and can clear doubts in next class.

• We will provide certificate if you are able to pass the final assessment with 80% marks.

• For more details drop a mail to given mail id by keeping the subject line as Query_ACS_101. Please expect a response within 24 hours.