How can you use SAS for data analysis?

1 Install and set up SAS

The first step is to install and set up SAS on your computer or access it online. Depending on your license and version, you may have different options to download and install SAS, such as SAS University Edition, SAS OnDemand for Academics, or SAS Studio. You can also use SAS Viya, a cloud-based platform that integrates with SAS and other languages. To set up SAS, you need to create an account, register your software, and configure your environment and preferences.

2 Import and explore data

The next step is to import and explore your data in SAS. You can use various methods to import data from different sources, such as Excel, CSV, text, or database files. You can use the Import Data wizard, the PROC IMPORT statement, or the LIBNAME statement to import data into SAS libraries and datasets. To explore your data, you can use the SAS Explorer window, the CONTENTS and PRINT procedures, or the SAS Studio tasks to view the structure, attributes, and values of your data.

3 Clean and transform data

The third step is to clean and transform your data in SAS. You can use various tools and techniques to check and correct errors, outliers, missing values, duplicates, and inconsistencies in your data. You can use the DATA step, the SORT and SQL procedures, or the SAS Studio tasks to manipulate and modify your data. You can also use the FORMAT and INFORMAT statements, the TRANSPOSE procedure, or the SAS Studio tasks to change the appearance and layout of your data.

4 Visualize and summarize data

The fourth step is to visualize and summarize your data in SAS. You can use various methods to create graphs, charts, tables, and reports that display and communicate your data effectively. You can use the SGPLOT and SGPANEL procedures, the ODS Graphics Designer, or the SAS Studio tasks to create graphical outputs. You can also use the MEANS, FREQ, TABULATE, and REPORT procedures, the ODS system, or the SAS Studio tasks to create statistical outputs.

5 Model and analyze data

The fifth step is to model and analyze your data in SAS. You can use various techniques to apply statistical or mathematical models to your data and test hypotheses, relationships, patterns, and trends. You can use the REG, ANOVA, GLM, LOGISTIC, and MIXED procedures, the SAS/STAT software, or the SAS Studio tasks to perform regression, analysis of variance, generalized linear models, logistic regression, and mixed models. You can also use the CLUSTER, FACTOR, PRINCOMP, and DISCRIM procedures, the SAS/IML software, or the SAS Studio tasks to perform cluster analysis, factor analysis, principal component analysis, and discriminant analysis.

6 Export and share data

The sixth and final step is to export and share your data in SAS. You can use various methods to export your data and results to different formats, such as Excel, CSV, text, or HTML files. You can use the Export Data wizard, the PROC EXPORT statement, or the ODS system to export data from SAS libraries and datasets. To share your data and results, you can use the SAS Drive, the SAS Content Server, or the SAS Viya platform to store, manage, and collaborate on your projects.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?