SAS is a Business Intelligence tool that facilitates analyses, reporting, data mining, and predictive modelling with the help of powerful visualizations and interactive dashboards.

Getting Started with Analytics

The following articles are for those who have a basic understanding of SAS Programming Language and want to learn Analytics to generate reports and perform analysis on the data.

Data analysis procedures such as proc univariate, proc means, proc freq are covered in these categories of articles.

K-Means Clustering in SAS

K-Means Clustering in SAS: an easy step-by-step guide

Cluster analysis is a type of multivariate data mining that groups items (like products, respondents, or other entities) based on characteristics or attributes chosen by the user.
It is the first and most crucial step in data mining. It is a common way to look at statistical data and is used in many different areas, such as data compression, machine learning, pattern recognition, and finding information.

One Way Anova in SAS

One Way Anova in SAS

The ANOVA, or analysis of variance, basically analyses the different estimates by utilising the F-distribution to evaluate if the population means are equal or not.

Proc Summary in SAS

Proc Summary in SAS: Explained

PROC SUMMARY in SAS procedures allows us to explore our data not only in terms of counts and distributions but also statistically. 

Box and Whisker Plot : Explained

Box and Whisker Plot : Explained

Box plots show the five-number summary of a set of data: the minimum score, first (lower) quartile, median, third (upper) quartile, and maximum score.

summarize categorical data

How to summarize categorical data graphically?

You can summarize categorical data by first sorting the values according to the categories of the variable. Then, placing the count, amount, or percentage of each category into a summary table or into one of several types of charts.

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