Explain statistical concepts like Hypothesis testing, and type 1 and type 2 errors.

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Hypothesis testing is a statistical method to test a claim about a population parameter. Type 1 error is rejecting a true null hypothesis, and type 2 error is failing to reject a false null hypothesis.

Hypothesis testing involves formulating a null hypothesis and an alternative hypothesis.
Type 1 error occurs when we reject a null hypothesis that is actually true.
Type 2 error occurs when we fail to reject a null hypothesis that is actually false.
The significance level (alpha) determines the probability of making a type 1 error.
The power of a test determines the probability of making a type 2 error.
Examples of hypothesis testing include testing the effectiveness of a new drug or testing the accuracy of a survey.

Explain statistical concepts like Hypothesis testing, and type 1 and type 2 errors.

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