## 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.

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

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.

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

Proc Univariate is a SAS procedures that calculate statistics for quantitative variables.

PROC FREQ in SAS is a procedure for analyzing the count of data. It is used to obtain frequency counts for one or more individual variables or to create two-way tables (cross-tabulations) from two variables.

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.

Business analytics is a set of statistical and operations research techniques, artificial intelligence, information technology and management strategies used for framing a business problem,, collecting data, and analysing the data to create value to organizations.

The Proc Tabulate procedure is used to create tables in SAS. Unlike Proc FREQ, this procedure can handle multiple variables in the row and column expressions. PROC TABULATE has a number of statements that define how this procedure will summarize the data.

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

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