Скачать или смотреть Clinical SAS Tutorials in Telugu - #15 Learn SAS Dataset Options |Great Online Training

Welcome to the 15th video in our Clinical SAS tutorial series (presented in Telugu). This beginner-friendly SAS Programming tutorial explains what SAS dataset options are and how to use them in real-world clinical data scenarios. The lesson is delivered in the Telugu language, making it easier for Telugu-speaking learners to grasp key SAS concepts while learning Clinical SAS techniques.

SAS dataset options are special parameters you can add to your data set references (e.g., in DATA or SET statements) to control how data is processed. They allow you to filter observations, select which variables to include or exclude, and even create indicator flags when combining datasets. Mastering these options will help you write cleaner, more efficient code – an essential skill in SAS Clinical programming and data management.

In this video, you will learn about several commonly used SAS dataset options and see examples of how they work. By the end of the tutorial, you’ll understand when and how to use these options in your SAS programs to manage datasets effectively.
(Note: The video’s instruction is in Telugu, but the concepts are explained step-by-step for beginners.)

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⏩Key Topics Covered:
🌕Introduction to SAS Dataset Options: What they are and why they’re useful in SAS programming (especially for Clinical SAS).
🌕WHERE= Option – How to use the WHERE= dataset option to subset data (filter rows based on a condition).
🌕DROP=/KEEP= Options – How to use DROP= and KEEP= options to exclude or include specific variables in a dataset.
🌕IN= Option – How to use the IN= option to create an indicator variable (flag) that shows whether an observation comes from a particular input dataset (useful in merging or combining datasets).
🌕Practical Examples: Demonstrations of each option with simple SAS code examples, explained in Telugu for easy understanding.

(No prior SAS experience is required — this tutorial is designed for beginners in Clinical SAS.)


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