What is normalization in statistics?
An example of an AI chatbot conversation about normalization in statistics.
What is normalization in statistics?
Normalization in statistics refers to the process of adjusting values in a dataset to a common scale, often to allow for comparison.
Why is normalization important?
Normalization is important because it helps to eliminate biases in data, making it easier to analyze and interpret results.
Can you give me an example of normalization?
Sure! For instance, if you have test scores ranging from 0 to 100 and you want to compare them to scores from another test ranging from 0 to 50, you can normalize both sets to a scale of 0 to 1.
What are the different methods of normalization?
Common methods include min-max normalization, z-score normalization, and decimal scaling, each serving different purposes.
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