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Q: What is a sample of hypothesis?
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What do you mean when you reject a hypothesis on the basis of sample?

alternitive hypothesis


Sample size must be equal for null hypothesis?

No.


What increases the chances of rejecting null hypothesis?

sample size


When do you accept a hypothesis?

You accept an alternative hypothesis when the p-value is greater than the sample a for a confidence level of 95%. The null hypothesis cannot be accepted.


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.


How does sample size affect your level of confidence in accepting a hypothesis?

A larger sample size generally leads to increased confidence in accepting a hypothesis, as it can provide more representative data and reduce the impact of random variability. However, the relationship between sample size and confidence levels also depends on factors like the variability within the data and the effect size of the hypothesis being tested.


What is the meaning of null hypthesis being rejected?

You may want to prove that a given statistic of a population has a given value. This is the null hypothesis. For this you take a sample from the population and measure the statistic of the sample. If the result has a small probability of being (say p = .025) if the null hypothesis is correct, then the null hypothesis is rejected (for p = .025) in favor of an alternative hypothesis. This can be simply that the null hypothesis is incorrect.


Testing of Hypothesis?

A hypothesis is a proposed explanation which scientists test with the available scientific theories. There are four steps to testing a hypothesis; state the hypothesis, formulate an analysis plan, analyze sample data and interpret the results.


The closer the sample mean is to the population mean?

Your question is a bit difficult to understand. I will rephrase: In hypothesis testing, when the sample mean is close to the assumed mean of the population (null hypotheses), what does that tell you? Answer: For a given sample size n and an alpha value, the closer the calculated mean is to the assumed mean of the population, the higher chance that null hypothesis will not be rejected in favor of the alternative hypothesis.


How do you know in question of hypothesis that there is population SD or sample SD?

da fac?


Why is important that a sample be random and representative when conducting hypothesis testing?

It helps you nawser


What is each sample does not necessarily have the same properties as every other sample?

You will typically have an experimental parameter that will be varied as part of testing a hypothesis.