## How to calculate Confidence Interval in SAS?

Learn how to calculate confidence intervals in SAS with our step-by-step guide. Discover different methods to obtain confidence intervals using procedures such as MEANS and UNIVARIATE, and explore how to interpret and use confidence intervals in your data analysis.

## 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.

## Bar Chart Examples: A Guide to create Bar Charts in SAS

A bar chart is an excellent way to visualize data. In this article, we’ll show you SAS bar chart examples and how…

## Step-by-Step Techniques to Understand Linear Regression

Linear Regression Importance. Read on to understand how to Prepare for a Linear Regression Analysis, its advantages and understanding Basic Concepts in Statistics

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

## 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.

## Why Standardization of variables is important?

Standardization of variables is the method of placing different variables on an identical scale thereby making it simpler to compare and analyze the data.