if it is unlikely to have happened by chance
Data is statistically significant if the p (probability) value is below a certain level (ex: 5% or 1%). The p value describes how often one would receive the results they got if left to chance alone. The lower the p value, the less likely it is that your results were due to chance and is stronger evidence against the null hypothesis. Also important to keep in mind is that just because something is statistically significant does not mean it is practically significant.
Statistically significant is the term used to define when two data are distinct enough in value as to be considered different values. To determine whether two data are close enough in value or distinct enough in value to be considered the same or different, usually you have to do a p-test or a t-test, depending on the type of data that you are looking at. Then confer with the corresponding chart for the test that you did to see whether or not the data is statistically significant.
No. However, the difference between them can be.
Yes!
No, it is not.
"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
if it is unlikely to have happened by chance
Data is statistically significant if the p (probability) value is below a certain level (ex: 5% or 1%). The p value describes how often one would receive the results they got if left to chance alone. The lower the p value, the less likely it is that your results were due to chance and is stronger evidence against the null hypothesis. Also important to keep in mind is that just because something is statistically significant does not mean it is practically significant.
Data is statistically significant if the p (probability) value is below a certain level (ex: 5% or 1%). The p value describes how often one would receive the results they got if left to chance alone. The lower the p value, the less likely it is that your results were due to chance and is stronger evidence against the null hypothesis. Also important to keep in mind is that just because something is statistically significant does not mean it is practically significant.
When people refer to an average, statisticians assume that they are referring to the arithmetic mean. That is, the sum of the individual observations divided by the number of observations. There are, in fact, several types of mean of which the arithmetic is just one (albeit the most commonly used).So statistically speaking, to be precise, you should probably say that the "arithmetic mean of a person in the U.S. is 22 years of age".
Statistically significant is the term used to define when two data are distinct enough in value as to be considered different values. To determine whether two data are close enough in value or distinct enough in value to be considered the same or different, usually you have to do a p-test or a t-test, depending on the type of data that you are looking at. Then confer with the corresponding chart for the test that you did to see whether or not the data is statistically significant.
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.