## Box and Whisker Plot : Explained

A box plot (also known as box and whisker plot) is a type of chart often used in descriptive data analysis to visually show the distribution of numerical data and skewness by displaying the data quartiles (or percentiles) averages. Box plots show the five-number summary of a set of data: the minimum score, first (lower) …

## 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.

## How to choose a statistical test?

If you are from a non-statistical background it is essentially the most complicated aspect of statistics, are always the basic statistical tests, and how to choose statistical test? In this article I have tried to mark out the distinction between the common statistical tests, the use of null value hypothesis in these tests by outlining …

## PROC TTEST for comparing means

PROC TTEST procedure is used to compare the equality of means for a one sample, two-sample (independent group) or paired t-test.

## Basics of Hypothesis Testing

Hypothesis testing is the statistical process of either retaining a claim or belief made by a person that is usually about population parameters such as mean or proportion and we seek evidence from a sample for the support of the claim.

## Confidence Interval for Population Mean

A confidence interval is constructed from a sample data is a range of values that is likely to include the population parameter with a certain probability.

The objective of a confidence interval is to provide location and precision of population parameters.

## Central Limit Theorem

Central Limit Theorem states that the sample means will be approximately normally distributed for large sample size regardless of the distribution from which the sample is taken.

## Descriptive Statistics in SAS with Examples

Descriptive Statistics is about finding “what has happened” by summarizing the data using statistical methods and analyzing the past data using queries.