Question

What aspect of avoiding Type I and Type II errors did you find most complexwhen it came to making a decision and interpreting the results? How do you think you could addressthese challenges in your future statistical research studies?

Answer 1

Answer :-

At the point when the null hypothesis is false and you neglect to dismiss it, you make a type II mistake. The probability of making a type II blunder is β, which relies upon the intensity of the test. You can diminish your danger of submitting a type II mistake by guaranteeing your test has enough power.

Hypothesis test is not 100% sure. Since the test depends on probabilities, there is consistently an opportunity of making a wrong end. When you complete a speculation test, two sorts of blunders are conceivable: type I and type II. The dangers of these two blunders are conversely related and dictated by the degree of centrality and the power for the test. Along these lines, you ought to figure out which mistake has increasingly serious ramifications for your circumstance before you characterize their dangers

The probability of rejecting the null hypothesis when it is false is equal to 1–β. This value is the power of the test.

You can diminish your danger of submitting a type II blunder by guaranteeing your test has enough power. You can do this by guaranteeing your example size is huge enough to distinguish a reasonable contrast when one really exists. The probabilities of dismissing the invalid theory when it is false is equivalent to 1–β.

Basically, in statistical theory testing a sort I mistake is the acknowledgment of a bogus speculation (otherwise called a "false positive" finding or decision), while a sort II blunder is the dismissal of a genuine theory (otherwise called a "false negative" finding or end).

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