Description
The course description covers the below topics in each chapter: This course will prepare you for SAS certifications. It will be a great start to enhance your career as a SAS programmer. Additional documents for better understanding and learning. Real world examples and working experience to the students. Creation of SAS Arrays and SAS Macros. Working with Temporary and Permanent library in SAS . Using PROC and SET statements . Basic terms and measures used in Statistics such as mean, median, mode, skewness, kurtosis, standard deviation and variance. Use of statistical procedures to analyze statistical data using SAS procedures. Descriptive statistics: Proc Means(Summary) with and without options, VAR and CLASS, PROC FREQ , PROC UNIVARIATE using data sets. All data sets are attached with the respective courses. Proc Correlation (Pearson moment correlation coefficient). Proc ANOVA (Example provided using p value to accept the null and alternate hypothesis). Explains hypothesis testing used in SAS using Proc t-test, predictive analytics such as linear regression, logistic regression. Clustering method in SAS using K-means method on an insurance dataset. Attached Data set. Creation of ARIMA model for forecasting the sales data. 2 Assignments for practice2 Quizzes to test the understanding of the students. Introduction to Big Data (Complimentary).
