Don't miss the piglix.com special BONUS offer during our Beta-test period. The next 100 new Registered Users (from a unique IP address), to post at least five (5) piglix, will receive 1,000 extra sign-up points (eventually exchangeable for crypto-currency)!

* * * * *    Free piglix.com Launch Promotions    * * * * *

  • Free Ads! if you are a small business with annual revenues of less than $1M - piglix.com will place your ads free of charge for up to one year! ... read more

  • $2,000 in free prizes! piglix.com is giving away ten (10) Meccano Erector sets, retail at $200 each, that build a motorized Ferris Wheel (or one of 22 other models) ... see details

Statistically significant


In statistical hypothesis testing,statistical significance (or a statistically significant result) is attained whenever the observed p-value of a test statistic is less than the significance level defined for the study. The p-value is the probability of obtaining results at least as extreme as those observed, given that the null hypothesis is true. The significance level, α, is the probability of rejecting the null hypothesis, given that it is true.

In any experiment or observation that involves drawing a sample from a population, there is always the possibility that an observed effect would have occurred due to sampling error alone. But if the p-value of an observed effect is less than the significance level, an investigator may conclude that that effect reflects the characteristics of the whole population, thereby rejecting the null hypothesis. A significance level is chosen before data collection, and typically set to 5% or much lower, depending on the field of study. This technique for testing the significance of results was developed in the early 20th century.

The term significance does not imply importance here, and the term statistical significance is not the same as research, theoretical, or practical significance. For example, the term clinical significance refers to the practical importance of a treatment effect.

In 1925, Ronald Fisher advanced the idea of statistical hypothesis testing, which he called "tests of significance", in his publication Statistical Methods for Research Workers. Fisher suggested a probability of one in twenty (0.05) as a convenient cutoff level to reject the null hypothesis. In a 1933 paper, Jerzy Neyman and Egon Pearson called this cutoff the significance level, which they named α. They recommended that α be set ahead of time, prior to any data collection.



...
Wikipedia

1,000 EXTRA POINTS!

Don't forget! that as one of our early users, you are eligible to receive the 1,000 point bonus as soon as you have created five (5) acceptable piglix.

...