The SurveySelect Procedure: How can I take a stratified random sample of my data?
More details, not necessarily found in the video, may be found in the description below:
The SURVEYSELECT Procedure
is a SAS programming procedure that provides flexibility and ease of use when you are in the sampling phase of your model building process. Utilizing the SAS data step for sampling is another option but a drawback is that it requires more understanding of SAS Programming.
You are encouraged to follow along and download the sample data-set that will be used in the video. You can download it here: https://www.kaggle.com/mlg-ulb/credit...
In this particular video, we will be utilizing stratified random sampling. We will use proc surveyselect to illustrate a strata example. We will also be using the srs method, also known as sampling without replacement. You can use method=urs, if you want to do sampling WITH replacement.
Stratified random sampling involves the division of a population into smaller groups, known as strata. This type of sampling is often utilized when we want to represent subgroups equally or proportionately within the sample.
As an example, Data scientists that deal with credit card fraud know that they have a lot more data for instances of no-fraud than actual fraud. Often, less than 0.05 of the data are instances of fraud. This creates a challenge for the modeling building process.
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