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Data Analysis [7-15]

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Classification Variable
(Proc Means)

Again, similar to Proc Univariate, you can specify the classification variables using the Class statement.
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Example

Data Cotton; Input ID Materials $ Origin $ Price; Datalines; 6501 Cotton China 7 6502 Cotton China 6.5 6503 Cotton China 17 6504 Cotton China 10 6505 Cotton China 8 6506 Cotton China 5.5 6507 Cotton China 3 6508 Cotton China 4.8 6509 Cotton China 9 6510 Cotton China 13 6511 Cotton Pakistan 21 6512 Cotton Pakistan 23 6513 Cotton Pakistan 27 6514 Cotton Pakistan 32 6515 Cotton Pakistan 12 6516 Cotton Pakistan 16 6517 Cotton Pakistan 14 6518 Cotton Pakistan 13.5 6519 Cotton Pakistan 17 6510 Cotton Pakistan 16.5 ; Run;

The COTTON data set contains the listed price of cotton from 20 different companies on Alibaba.com. 

Of the 20 companies listed, 10 are from China and the other 10 are from Pakistan.

Let's take a look at how you can analyze the cotton price from the two countries.

Example

Proc Means Data=Cotton;
Var Price;
Class Origin;
Run;

The CLASS statement is added to Proc Means specifying the variable Origin as the classification variable.

The analysis will be separated for the two origins.

BY Statement

You can also use the BY statement to separate the analysis into different groups.

Example

Proc Sort Data=Cotton;
By Origin;
Run;

Proc Means Data=Cotton;
Var Price;
By Origin;
Run;

This will generate similar results as using the CLASS statement:

Note: the Class statement is generally preferred, as it does not require data set to be sorted prior to running the procedure.

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Exercise

Compute the range, Q1, median and Q3 statistics on the cotton prices between the two origins.

Next

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Need some help? 

Get Hint

HINT:
Either the Class statement or By statement works.

Get Solution

SOLUTION:
Proc Means Data=Cotton Range Q1 Median Q3;
Var Price;
Class Origin;
Run;

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