SAS is in the market for around 2 decades & has become an industry leader for providing a new generation of business intelligence software. It is the most popular tool for commercial analytics & has strong statistical features. This software allows you to generate insights even from the most complex data.

Despite the popularity of data science, advanced analytics is something a majority of the world is yet not completely familiar with. The knowledge of this tool empowers you to leverage data & data science for advanced analytics that can help any organization significantly.

Considering the importance of this software, we have curated this course that will help you to learn various concepts revolving around statistics & data analysis. You will implement all the concepts in real-time using SAS Studio Software. Upon completion, you will be confident in working with SAS for your upcoming projects.

Why This Course Is Unique?

This course will help you in understanding SAS & using it for any given project from scratch. To make it simple for you, the instructors have divided all the sections of this course in 2 parts. Content covered in the 1st part will help you in learning from the data. The 2nd part will be the most advanced part that will cover the probability and statistical inference, as well as how to create and interpret linear regression and ANOVA models.

All and all, with this SAS course, you will learn – graphical and numerical methods for describing data, basic probability distributions, methods for describing bivariate data, basic probability concepts, significance tests, hypothesis testing, linear regression, and analysis of variance.

This Course Includes:

• Introduction to data

• Population & sample, variable types, sources of bias

• Data stimulation in SAS & calculation margin of error

• Bar charts, histograms, box plots, Q-Q plots

• Relationship between mean, median, skewness, and standard deviations

• Understanding bivariate data sets

• Probability: Distributions and thinking about the chance

• Inference: Hypothesis Testing and Statistical Significance

• Modeling: Linear regression and analysis of variance

• A project involving univariate and bivariate analyses, linear model

Leverage the power of advanced analytics with SAS – Get started now from scratch!!