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What else can I help you with?
Is there a direct relationship between the power of a test and the probability of a Type II error?
The power of a test is 1 minus the probability of a Type II error.
If the probability of type 1 error is reduced the probability of type 2 error is also reduced?
No....the two are mirror images of each other. Reducing type I would increase type II
What is the probability that type 1 error will be made z -2.575 or z 2.575?
The probability is 0.005012, approx.
What is the probability that type 1 error will be made for z -2.33 or z 2.33?
2%
Reduce type 1 error?
Accept lower p-values (meaning lower in magnitude; values tending toward zero).--And don't forget that by reducing the probability of getting a type I error, you increase the probability of getting a type II error (inverse relationship).
Is there a direct relationship between the power of a test and the probability of a Type II error?
The power of a test is 1 minus the probability of a Type II error.
If the probability of type 1 error is reduced the probability of type 2 error is also reduced?
No....the two are mirror images of each other. Reducing type I would increase type II
What is the probability that type 1 error will be made z -2.575 or z 2.575?
The probability is 0.005012, approx.
If a test of hypothesis has a type 1 error probability 01?
If the type 1 error has a probability of 01 = 1, then you will always reject the null hypothesis (false positive) - even when the evidence is wholly consistent with the null hypothesis.
What is the probability that type 1 error will be made for z -2.33 or z 2.33?
2%
Reduce type 1 error?
Accept lower p-values (meaning lower in magnitude; values tending toward zero).--And don't forget that by reducing the probability of getting a type I error, you increase the probability of getting a type II error (inverse relationship).
What is the probability of making type 1 error when null hypothesis is true?
It is the same as the significance level of the test - often 5%.
Relationship between type 1 error and type 2 error?
In statistics, there are two types of errors for hypothesis tests: Type 1 error and Type 2 error. Type 1 error is when the null hypothesis is rejected, but actually true. It is often called alpha. An example of Type 1 error would be a "false positive" for a disease. Type 2 error is when the null hypothesis is not rejected, but actually false. It is often called beta. An example of Type 2 error would be a "false negative" for a disease. Type 1 error and Type 2 error have an inverse relationship. The larger the Type 1 error is, the smaller the Type 2 error is. The smaller the Type 2 error is, the larger the Type 2 error is. Type 1 error and Type 2 error both can be reduced if the sample size is increased.
Does the probability of the type 1 error increase as the sample size increases?
No, the estimates should become more robust and the power of the test should, therefore, increase.
What is the probability 10?
Probability = 10 is a very serious mistake since the probability of any event can never be greater than 1: so a probability of 10 is obviously a big error.
What type of event is Theoretical probability of 1?
Theoretical probability of 1 refers to an event that is certain to happen. It has a probability of 1 because it is guaranteed to occur.
What type of answer will you get for every probability problem?
The answer will be 1.
