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#Statistical calculations are extensively done with quizlet trial

Consider the same examples as above for convenience.What ultimately happens here is that the true null hypothesis is wrongly accepted even if it is false.It indicates the failure of being able to accept the alternative hypothesis.It is also called ‘false negative’ or ‘beta error’.In other words, it occurs when we try to ignore something that actually exists.It occurs when a null hypothesis is not rejected when it is actually false.If he is convicted for something he has not done, a type 1 error has occurred. If it is true, he will be let free, and it will be the correct decision.The null hypothesis would be a statement, like ‘He is innocent’.

#Statistical calculations are extensively done with quizlet trial

Another example would be to consider the trial of a person accused of murder.

Therefore, the null hypothesis is true in this case, but is being rejected due to false effect.

Contrary to this, if your dish tastes great, it would automatically be assumed that it is so because of the extra ingredient, when in reality, it is not.

Therefore, the null hypothesis would be ‘Adding this ingredient has no effect on the taste’.

In this case, the truth of taste improvement in the dish is tested.

Suppose you decide to bake lasagna, and you add an extra ingredient (assuming it will enhance the taste), that is actually not supposed to be added.

So, ultimately, what happens is that the true null hypothesis is wrongly rejected even if it is true.

It indicates the acceptance of the alternative hypothesis.

It is also called ‘false positive’ or ‘alpha error’.

In other words, it occurs when we try to find out something that does not possibly exist at all.It occurs when a null hypothesis is rejected when it is actually true.