Complete SAS Programming Guide - Learn SAS and Become a Data Ninja - Important Housekeeping

Complete SAS Programming Guide - Learn SAS and Become a Data Ninja - Important Housekeeping

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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The video tutorial covers data cleaning techniques using SAS programming. It begins with converting a response variable from character to binary format, followed by renaming variables. The tutorial then demonstrates converting character variables to numeric using the input function. It also explains removing unwanted characters from variables using the compress function. Finally, similar changes are applied to a test dataset, excluding the response variable conversion.

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7 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of transforming a response variable from categorical to binary?

To enable numerical calculations

To make it easier to read

To improve data visualization

To reduce data size

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which SAS statement is used to create a new dataset and read an existing one?

Merge statement

Data statement

Set statement

Proc statement

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of using an 'if-then' statement in SAS?

To perform conditional operations

To drop variables

To rename variables

To merge datasets

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which function is used to convert a character variable to a numeric variable in SAS?

Compress function

Output function

Input function

Format function

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is an informat needed when converting a character variable to a numeric one?

To indicate the variable length

To specify the variable name

To provide a format for numbers

To define the data type

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the compress function in SAS?

To convert data types

To rename variables

To remove unwanted characters

To merge datasets

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is it important to apply the same data transformations to both training and test datasets?

To enhance readability

To reduce data size

To ensure consistency

To improve visualization