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What else can I help you with?
What do you mean when you reject a hypothesis on the basis of sample?
alternitive hypothesis
Why is important that a sample be random and representative when conducting hypothesis testing?
It helps you nawser
What is hypothesis of difference?
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.
How is sampling distribution used in the process of hypothesis testing?
Sampling distribution is crucial in hypothesis testing as it provides the distribution of a statistic, such as the sample mean, under the null hypothesis. By understanding the sampling distribution, researchers can determine the likelihood of obtaining their observed sample statistic if the null hypothesis is true. This allows for the calculation of p-values, which indicate the probability of observing the data given the null hypothesis. Ultimately, this helps in making informed decisions about whether to reject or fail to reject the null hypothesis.
What role does Random Sampling Distribution in hypothesis testing?
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.
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?
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.
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.
Why is important that a sample be random and representative when conducting hypothesis testing?
It helps you nawser
How do you know in question of hypothesis that there is population SD or sample SD?
da fac?
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.
