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What can power analysis be used to calculate?
Power analysis can be used to calculate statistical significance. It compares the null hypothesis with the alternative hypothesis and looks for evidence that can reject the null hypothesis.
What is null hypothsis?
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
Is the null hypothesis considered correct until proven otherwise?
No. The null hypothesis is not considered correct. It is an assumption, and hypothesis testing is a consistent meand of determining whether the data is sufficiently strong to say that it may be untrue. The data either supports the alternative hypothesis or it fails to reject it. See examples in links. Also note this quote from Wikipedia: "Statistical hypothesis testing is used to make a decision about whether the data contradicts the null hypothesis: this is called significance testing. A null hypothesis is never proven by such methods, as the absence of evidence against the null hypothesis does not establish it."
Explain what is meant by null hypothesis?
The null hypothesis is an hypothesis about some population parameter. The goal of hypothesis testing is to check the viability of the null hypothesis in the light of experimental data. Based on the data, the null hypothesis either will or will not be rejected as a viable possibility.
Type 1 error and type 2 error?
In statistics: type 1 error is when you reject the null hypothesis but it is actually true. Type 2 is when you fail to reject the null hypothesis but it is actually false. Statistical DecisionTrue State of the Null HypothesisH0 TrueH0 FalseReject H0Type I errorCorrectDo not Reject H0CorrectType II error
What can power analysis be used to calculate?
Power analysis can be used to calculate statistical significance. It compares the null hypothesis with the alternative hypothesis and looks for evidence that can reject the null hypothesis.
How is z score and p value related?
The z-score is a statistical test of significance to help you determine if you should accept or reject the null-hypothesis; whereas the p-value gives you the probability that you were wrong to reject the null-hypothesis. (The null-hypothesis proposes that NO statistical significance exists in a set of observations).
What null hypothsis?
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
What is null hypothsis?
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
What is an alternative hypothesis?
with the alternative hypothesis the reasearcher is predicting
What does the researcher hope to do with null hypothesis (the opposite ofthe research hypothesis)?
In fact, any statistical relationship in a sample can be interpreted in two ways: ... The purpose of null hypothesis testing is simply to help researchers decide ... the null hypothesis in favour of the alternative hypothesis—concluding that there is a ...
Is the correct definition of Power of a test (Note Ho null hypothesis Ha alternative hypothesis)?
No, that is not the correct definition.
How is null hypothesis tested?
The null hypothesis is typically tested using statistical tests such as t-tests, ANOVA, or chi-square tests. These tests calculate the probability of obtaining the observed data if the null hypothesis were true. If this probability (p-value) is below a certain threshold (usually 0.05), the null hypothesis is rejected.
What is the power of a statistical test?
The power of a statistical test is the probability that the test will reject the null hypothesis when it is, in fact, false. Please see the link.
The term statistical significance implies that the results are?
The observed value is unlikely to have occured purely bt chance under the null hypothesis and, as a consequence, you ought to reject the null in favour of the alternative hypothesis.
Why have a null hypothesis?
Statistical tests are designed to test one hypothesis against another. Conventionally, the default hypothesis is that the results were obtained purely by chance and that there is no observed effect acting on the observations - ie the effect is null. The alternative is that there IS an effect.
Why you need to write hypothesis in directional non directional and null directional?
Because the statistical test will compare the probability of the outcome under the null hypothesis in relation to the outcome under either a dierectional or non-directional alternative hypothesis.
