This question lacks the details to make any judgement.
"Statistically significant" means that the result is beyond the element of chance.
A result is statistically significant if:it is unlikely to have occurred by chance
No, it is not.
There is nothing particularly significant about a sample size of 30.
Those that are statistically significant.
"Statistically significant" means that the result is beyond the element of chance.
A result is statistically significant if:it is unlikely to have occurred by chance
No, it is not.
if it is unlikely to have happened by chance
No. However, the difference between them can be.
A number, by itself, cannot be statistically significant. It is necessary to know what the underlying statistical distribution for that number is. That information can be obtained from knowledge of the statistical test being carried out.
You buy a thousand lottery tickets (different numbers) and win nothing. That is statistically significant because the chances of that happening purely by chance are pretty slim. But if the lottery is operated properly, the result is not practically significant. There is nothing that can be done. Tough!
There is nothing particularly significant about a sample size of 30.
Statistical significance is determined by comparing a p-value to a predetermined significance level, often set at 0.05. A p-value of 0.001 indicates a result that is highly statistically significant, as it suggests a less than 0.1% probability that the observed effect is due to chance. Thus, if this p-value is derived from a relevant analysis, it would typically be considered statistically significant.
Those that are statistically significant.
Yes!
Whether 0.045 is statistically significant depends on the context, specifically the predetermined significance level (alpha) for the analysis. Commonly, a p-value of 0.05 is used as a threshold, meaning that a p-value of 0.045 would be considered statistically significant, indicating strong evidence against the null hypothesis. However, it's essential to consider the study design, sample size, and practical significance when interpreting this result.