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If a test of hypothesis has a type I error probability of 0.01 it means?
Wiki User
∙ 6y ago
It means that, if the null hypothesis is true, there is still a 1% chance that the outcome is so extreme that the null hypothesis is rejected.
Wiki User
∙ 6y ago
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A chi square probability of 0.05 means what?
If your chi square test has a probability of 0.05 or less it is likely, but not certain, that your hypothesis is not correct.
What is the meaning of hypothesis in statistics?
A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.
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.
How is the power of a statistical test defined?
The power of a statistical test is defined as being a probability that a test will product a result that is significantly different. It can be defined as equaling the probability of rejecting the null hypothesis.
What is the probability of making a Type II error if the null hypothesis is actually true?
zero. We have a sample from which a statistic is calculated and will challenge our held belief or "status quo" or null hypothesis. Now you present a case where the null hypothesis is true, so the only possible error we could make is to reject the null hypothesis- a type I error. Hypothesis testing generally sets a criteria for the test statistic to reject Ho or fail to reject Ho, so both type 1 and 2 errors are possible.
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.
When you reject the Null Hypothesis that means that the Null Hypothesis cannot be correct?
No. Rejecting the Null Hypothesis means that there is a high degree of probability that it is not correct. This degree of probability is the critical level that you choose for the test statistic. However, there is still a small probability that the null hypothesis was correct.
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%.
A chi square probability of 0.05 means what?
If your chi square test has a probability of 0.05 or less it is likely, but not certain, that your hypothesis is not correct.
What is the meaning of hypothesis in statistics?
A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.
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.
How is the power of a statistical test defined?
The power of a statistical test is defined as being a probability that a test will product a result that is significantly different. It can be defined as equaling the probability of rejecting the null hypothesis.
What does the hypothesis test?
to test a hypothesis means to evaluate the gathered facts with the help of an experiment
What is the probability of making a Type II error if the null hypothesis is actually true?
zero. We have a sample from which a statistic is calculated and will challenge our held belief or "status quo" or null hypothesis. Now you present a case where the null hypothesis is true, so the only possible error we could make is to reject the null hypothesis- a type I error. Hypothesis testing generally sets a criteria for the test statistic to reject Ho or fail to reject Ho, so both type 1 and 2 errors are possible.
What does the p value have to be for you to reject it in chi square conclusions?
The p value for rejecting an hypothesis is more closely related to the type of errors and their consequences. The p value is not determined by the chi square - or any other - test but by the impact of the decision made on the basis of the test. The two types of errors to be considered are: what is the probability that you reject the null hypothesis when it is actually true (type I error), and what is the probability that you accept the null hypothesis when, in fact, it is false (type I error).. Reducing one type of error increase the other and there is a balance to be struck between the two. This balance will be influenced by the costs associated with making the wrong error. In real life, the effects (costs/benefits) of decisions are very asymmetrical.
What does test the hypothesis mean?
to test a hypothesis means to evaluate the gathered facts with the help of an experiment
How do scientists use statistics when they test a hypothesis?
When testings a hypothesis, statistics can be used to calculate the chances or probability of getting a result
