Type 1 vs Type 2 Errors Explained 🔥 Statistics & Machine Learning

🔥 Do you know, Type 1 and Type 2 errors are one of the most fundamental concepts in Statistics, specific to Hypothesis Testing. As an aspiring Data Scientist and Data Analyst, you will often be asked about these two terms during interviews. This Short is the only reference material you would ever need on Type 1 and Type 2 Errors ever.

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From a technical standpoint, here are the broader details of these concepts:

👉 Null Hypothesis (Ho)
- It is a general statement or a default position
- In the video, null hypothesis is: Person is not pregnant
- It assumes that there is no significant difference, effect, or relationship between variables being studied (like Criminal/Not Criminal or Pregnant/Not Pregnant).

👉 Alternative Hypothesis (Ha)
- Ha suggests that there is indeed a specific difference, effect, or relationship.

👉 Type 1 Error
- Occurs when we mistakenly reject a null hypothesis
- Example from the video: Man diagnosed pregnant is Type 1 Error
- This error is often referred to as a "false positive" or a "false alarm."

👉 Type 2 Error
- Occurs when we fail to reject a null hypothesis
- Example from the video: Pregnant Woman diagnosed as not pregnant is Type 2 Error
- In this case, we accept the null hypothesis as true when it is actually false
- Type 2 errors are also known as "false negatives."

To summarize, Type 1 and Type 2 errors highlight the trade-off between making correct decisions and the risk of making errors. By grasping these concepts, you can navigate interviews with confidence and apply robust data analysis techniques in your future endeavors.

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[Analyticsvidhya]

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[monilvalia]

He is NOT GUILTY as our hypothesis.

So in reality if he is not guilty, he is TYPE 1 ERROR means our null hypothesis is right. Which is- there is no difference between reality and hypothesis.

BUT IF IN REALITY HE IS FOUND GUILTY, IT'S TYPE 2 ERROR, Means our null hypothesis is wrong.

[subratkumarsahoo]

Type 1 also doctor should be saying you are not pregnant... Please correct your image or slide😊😊