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The null and alternative hypotheses are not calculated. They should be determined before any data analyses are carried out.

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Q: How to calculate the null and alternative hypothesis and test 5 level of significance?
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In a hypothesis testing the alternative hypothesis is assumed?

No. The null hypothesis is assumed to be correct unless there is sufficient evidence from the sample and the given criteria (significance level) to reject it.


What is another name for the probability of observing a sample value at least as extreme as a given on under a null hypothesis?

The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis.


Which is better a 0.05 level of significance or 0.01 level of significance?

0.05 level of significance indicates that there is a 5% chance (0.05) that, under the null hypothesis, the observation could have occurred by chance. The 0.01 level indicates that there is a much smaller likelihood of the event occurring purely by chance - much stronger evidence for rejecting the null hypothesis in favour of the alternative hypothesis.


Can you accept a null hypothesis under the t statistic and then reject the same null hypothesis using the F statistic?

At the same level of significance and against the same alternative hypothesis, the two tests are equivalent.


List the 5 steps of hypothesis testing and explain the procedure and logic of each Specify the null and alternative hypothesis Select a significance level typically 0.05 or the 0.01 level is used?

what is an example of a hypothses about compensation?


Differences between null and alternative hypothesis?

The difference between the null hypothesis and the alternative hypothesis are on the sense of the tests. In statistical inference, the null hypothesis should be in a positive sense such in a sense, you are testing a hypothesis you are probably sure of. In other words, the null hypothesis must be the hypothesis you are almost sure of. Just an important note, that when you are doing a tests, you are testing if a certain event probably occurs at certain level of significance. The alternative hypothesis is the opposite one.


Why is the level of significance always small?

The significance level is always small because significance levels tell you if you can reject the null-hypothesis or if you cannot reject the null-hypothesis in a hypothesis test. The thought behind this is that if your p-value, or the probability of getting a value at least as extreme as the one observed, is smaller than the significance level, then the null hypothesis can be rejected. If the significance level was larger, then statisticians would reject the accuracy of hypotheses without proper reason.


What does the critical value represent?

The critical value is used to test a null hypothesis against an alternative hypothesis at some pre-defined level of significance. A test statistic is calculated from the outcomes of a set of trials and if this test statistic is more extreme than the critical value then the null hypothesis must be rejected in favour of the alternative.


What is the p-value if 0.01 is the level of significance and the mean is 18688 and the standard deviation is 15500?

In order to solve this you need the null hypothesis value also level of significance only helps you decide whether or not to reject the null hypothesis, is the p-value is above this then you do not reject the null hypothesis, if it is below you reject the null hypothesis Level of significance has nothing to do with the math


When should you accept a null hypothesis?

The null hypothesis cannot be accepted. Statistical tests only check whether differences in means are probably due to chance differences in sampling (the reason variance is so important). So if the p-value obtained by the data is larger than the significance level against which you are testing, we only fail to reject the null. If the p-value is lower than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis.


What is the mean of a null hypothesis being rejected?

the hypothesis might be correct* * * * *The available evidence suggests that the observations were less likely to have been obtained from random variables that were distributed according to the null hypothesis than under the alternative hypothesis against which the null was tested.


Is The probability at which the null hypothesis can be rejected with confidence is known as level of significance?

Yes.