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What do you mean when you reject a hypothesis on the basis of sample?
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∙ 12y ago
alternitive hypothesis
Wiki User
∙ 12y ago
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What does it mean when a scientist fails to reject a hypothesis?
It means that the experiment is consistent with the hypothesis. It adds to the credibility of the hypothesis.
How do you calculate distribution of sample means?
The sample mean is distributed with the same mean as the popualtion mean. If the popolation variance is s2 then the sample mean has a variance is s2/n. As n increases, the distribution of the sample mean gets closer to a Gaussian - ie Normal - distribution. This is the basis of the Central Limit Theorem which is important for hypothesis testing.
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
What are difference between a hypothesis and hypothesis statement?
The term hypothesis is used in science and statistics. I have included two links related to the these terms.In statistics, the null and alternative hypothesis are mathematical statements used in statistical decision making. An example of a null hypothesis is the mean of the population from which a sample was obtained is equal to 10. The mean of the data is sufficiently different from 10 can be used to reject the null hypothesis.As used in science, hypothesis is the initial idea suggested by observation or preliminary experimentation. See related links.
When the observed sample mean is close to expected population mean what do you in terms of the null hypothesis?
It depends on whether the hypothesis concerns the mean or the standard error (or variance) or something else.
What does it mean when a scientist fails to reject a hypothesis?
It means that the experiment is consistent with the hypothesis. It adds to the credibility of the hypothesis.
If the chi-square is very large what does it mean?
The null hypothesis in a chi-square goodness-of-fit test states that the sample of observed frequencies supports the claim about the expected frequencies. So the bigger the the calculated chi-square value is, the more likely the sample does not conform the expected frequencies, and therefore you would reject the null hypothesis. So the short answer is, REJECT!
How do you calculate distribution of sample means?
The sample mean is distributed with the same mean as the popualtion mean. If the popolation variance is s2 then the sample mean has a variance is s2/n. As n increases, the distribution of the sample mean gets closer to a Gaussian - ie Normal - distribution. This is the basis of the Central Limit Theorem which is important for hypothesis testing.
When a random sample of 64 bottles of the 200 count Bayer Aspirin showed a mean turnover rate of 5.84 Shall you reject the hypothesis that the population mean is 6.0?
You cannot, because you have no information on the variance or standard error.
What dose it mean if a scientist fails to reject a hypothesis?
It means there is no reason why he should reject it, whether because there is no evidence to the contrary or because an experiment set up to test it affirmed that hypothesis.
What dose it mean if a scientists fails to reject a hypothesis?
It means there is no reason why he should reject it, whether because there is no evidence to the contrary or because an experiment set up to test it affirmed that hypothesis.
What dose it mean if a scientist fail to reject a hypothesis?
It means there is no reason why he should reject it, whether because there is no evidence to the contrary or because an experiment set up to test it affirmed that hypothesis.
What does it mean if a scientist can't reject a hypothesis?
It means that she or he has to accept that the existing hypothesis appears to be true.
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.
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
What are difference between a hypothesis and hypothesis statement?
The term hypothesis is used in science and statistics. I have included two links related to the these terms.In statistics, the null and alternative hypothesis are mathematical statements used in statistical decision making. An example of a null hypothesis is the mean of the population from which a sample was obtained is equal to 10. The mean of the data is sufficiently different from 10 can be used to reject the null hypothesis.As used in science, hypothesis is the initial idea suggested by observation or preliminary experimentation. See related links.
When the observed sample mean is close to expected population mean what do you in terms of the null hypothesis?
It depends on whether the hypothesis concerns the mean or the standard error (or variance) or something else.
