alternitive hypothesis
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The alternativehypothesis (Ha or H1) describes the population parameters that the sample data represent, if the predicted relationship exists. It is always the hypothesis of difference. That is as opposed to the null hypothesis (H0) that describes the population parameters that the sample data represent if the predicted relationship does not exist. See Basic Statistics of the Behavioral Sciences by Heiman.
It is an assumption to hypothesis testing. I can not comment on the significance of a violation of these assumptions without knowing how the non-random sample was taken.
It depends on whether the hypothesis concerns the mean or the standard error (or variance) or something else.
alternitive hypothesis
No.
The larger the sample size the more confident you can be that the data you have collected is representative of what would happen on a larger scale. So if your results seem to prove your hypothesis right then the larger you sample size the more confident you can be in accepting your hypothesis.
sample size
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.
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.
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.
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.
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.
da fac?
sample statistic
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