What is Statistical Significance?
The for a given hypothesis test is a value for which a less than or equal to is considered statistically significant.
Statistical significance does not mean practical significance.
Fortunately, you can easily determine the statistical significance of experiments, without any math, using , the advanced statistical model builtin to Optimizely.
After you do a statistical test, you are either going to reject or accept the null hypothesis. Rejecting the null hypothesis means that you conclude that the null hypothesis is not true; in our chicken sex example, you would conclude that the true proportion of male chicks, if you gave chocolate to an infinite number of chicken mothers, would be less than 50%.
Now say statistically significant three times fast.
Since sample size is so important in making statistical inferences, your committee naturally wants to be sure that your dissertation research uses an adequate sample size to effectively address your research questions. That is why you should include a "sample size justification" section in your .
Power Analysis is a family of statistical procedures which are used to justify the appropriate sample size for testing a given statistical hypothesis.
Statistical significance  Wikipedia
Power Analysis is a family of statistical procedures which are used to justify the appropriate sample size for testing a given statistical hypothesis.
Since sample size is so important in making statistical inferences, your committee naturally wants to be sure that your dissertation research uses an adequate sample size to effectively address your research questions. That is why you should include a "sample size justification" section in your .
Statistical Significance  Online and Paper Surveys

What does "statistical significance" really mean
Statistically significant.

Pvalue, significance level and hypothesis
In principle, a statistically significant result (usually a difference) is a result that’s not attributed to chance.

26/06/2017 · How to Assess Statistical Significance
19/03/2015 · Understanding Hypothesis Tests: Significance Levels (Alpha) and P values in Statistics
Sample Size  Statistically Significant Consulting
My tutorial page provides a good explanation of the basic principles of probability and statistical inference. If you understand those concepts, you will understand why sample size is so important to the effectiveness of your study.
sample size for testing a given statistical hypothesis ..
Except that... there is a justification for onetailed tests after all. You just interpret the p value differently. P values for onetailed tests are half those for twotailed tests. It follows that the p value from a onetailed test is the exact probability that the true value of the effect has opposite sign to what you have observed, and 1  p is the probability that the true value of the effect has the same sign, as I explained . Hey, we don't have to muck around with p/2. So here's what you could write in the Methods section of your paper: "All tests of significance are onetailed in the direction of the observed effect. The resulting p values represent the probability that the true value of the effect is of sign opposite to the observed value." Give it a go and see what happens. Such a statement would be anathema to reviewers or statisticians who assert that an observed positive result is not a justification for doing a onetailed test for a positive result. They would argue that you are downgrading the criterion for deciding what is "statistically significant", because you are effectively performing tests with a Type I error of 10%. Fair enough, so don't mention statistical significance at all. Just show 95% confidence limits, and simply say in the Methods: "Our p values, derived from onetailed tests, represent the probability that the true value of the effect is of sign opposite to the observed value."
Statistical Significance  PalaeoElectronica
My tutorial page provides a good explanation of the basic principles of probability and statistical inference. If you understand those concepts, you will understand why sample size is so important to the effectiveness of your study.
TTest Statistical Significance Example and Definition
Statistical significance is a measure of whether your research findings are meaningful. More specifically, it’s whether your stat closely matches what value you would expect to find in an entire . In order to test for statistical significance, perform these steps:
An explanation of statistical significance in the context ..
Whilst there is relatively little justification why a significance level of 0.05 is used rather than 0.01 or 0.10, for example, it is widely used in academic research. However, if you want to be particularly confident in your results, you can set a more stringent level of 0.01 (a 1% chance or less; 1 in 100 chance or less).