How do you explain the concept of degrees of freedom in a t-test?
Understanding the concept of degrees of freedom (DF) is crucial when performing a t-test in data science. This statistical term is often shrouded in confusion, but it's essentially the number of independent values that can vary in an analysis without breaking any constraints. In the context of a t-test, which is used to determine if there are significant differences between two sample means, degrees of freedom help to fine-tune the critical values from the t-distribution, which is a key step in deciding whether to reject the null hypothesis.
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Prithvi SeshadriData Science @Shell | Microsoft Certified Data Scientist | Vellore Institute of Technology
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