SAS Analytics

Meet the Instructor 1 lecture 01:10 Instructor Portfolio Meet the Instructor 1 lecture 01:10 Instructor Portfolio Instructor Portfolio Instructor Portfolio Instructor Portfolio Instructor Portfolio Introduction to Business Analytics 2 lectures 19:42 What is Business Analytics ? What are the three main categories of Analytics? Introduction to Business Analytics 2 lectures 19:42 What is Business Analytics ? What are the three main categories of Analytics? What is Business Analytics ? What is Business Analytics ? What is Business Analytics ? What is Business Analytics ? What are the three main categories of Analytics? What are the three main categories of Analytics? What are the three main categories of Analytics? What are the three main categories of Analytics? Installation of SAS 1 lecture 14:11 Installation Installation of SAS 1 lecture 14:11 Installation Installation Installation Installation Installation Linear Regression-Concepts 3 lectures 22:32 Concept of Linear Regression Assumptions of Classical Linear Regression Model Concept of Multi colinearity and Auto corelation Linear Regression-Concepts 3 lectures 22:32 Concept of Linear Regression Assumptions of Classical Linear Regression Model Concept of Multi colinearity and Auto corelation Concept of Linear Regression Concept of Linear Regression Concept of Linear Regression Concept of Linear Regression Assumptions of Classical Linear Regression Model Assumptions of Classical Linear Regression Model Assumptions of Classical Linear Regression Model Assumptions of Classical Linear Regression Model Concept of Multi colinearity and Auto corelation Concept of Multi colinearity and Auto corelation Concept of Multi colinearity and Auto corelation Concept of Multi colinearity and Auto corelation Linear Regression-Practical sessions 6 lectures 01:07:09 Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Case Study & Data Set Discussion of Linear Regression Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-2 A. Checking for auto correlationB. Checking for Heteroscedasticity and auto correlation Linear Regression-Practical sessions. 6 lectures 01:07:09 Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Case Study & Data Set Discussion of Linear Regression Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-2 A. Checking for auto correlationB. Checking for Heteroscedasticity and auto correlation Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-3 A. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) techniqueA. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) techniqueA. Dividing the data into two parts, training and validationB. Running the Regression procedure on training data and doing Stepwise Selection using Adjusted R2 (square) technique Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-4 A. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training dataA. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training dataA. Specifying all the significant independent variables from the above result and predicting the dependent variable for the training dataB. Finding the correlation between the observed value and predicted value of our dependent variable from the training data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Linear Regression Practical-5 A. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation dataA. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation dataA. Predicting the dependant variable for the validation dataB. Finding correlation between the observed and predicted value of our dependent variable from the validation data Case Study & Data Set Discussion of Linear Regression Case Study & Data Set Discussion of Linear Regression Case Study & Data Set Discussion of Linear Regression Case Study & Data Set Discussion of Linear Regression Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-1 A. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variablesA. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variablesA. Creating the library to access the data setsB. Running Regression procedure and checking the multi collinearity of independent variables Linear Regression Practical-2 A. Checking for auto correlationB. Checking for Heteroscedasticity and auto correlation Linear Regression Practical-2 A. Checking for auto correlationB...