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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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What are the three parts of a hypotnesis statement?

A hypothesis statement consists of three parts: the null hypothesis (H0), the alternative hypothesis (Ha), and the level of significance (alpha). The null hypothesis states that there is no relationship or difference between variables, while the alternative hypothesis suggests the presence of a relationship or difference. The level of significance determines the threshold for accepting or rejecting the null hypothesis based on statistical testing.


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.


How is H1 hypothesis rejected?

H1 hypothesis is rejected when the p-value associated with the test statistic is less than the significance level (usually 0.05) chosen for the hypothesis test. This indicates that the data provides enough evidence to reject the alternative hypothesis in favor of the null hypothesis.


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.


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.


Why null hypothesis it is tested at 0.05 level of significance?

A significance level of 0.05 is commonly used in hypothesis testing as it provides a balance between Type I and Type II errors. Setting the significance level at 0.05 means that there is a 5% chance of rejecting the null hypothesis when it is actually true. This level is widely accepted in many fields as a standard threshold for determining statistical significance.


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