In statistical significance testing, the p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. If the p-value is less than 0.05 or 0.01, corresponding respectively to a 5% or 1% chance of rejecting the null hypothesis when it is true (Type I error).

SELECT deptno, count(deptno)

FROM emp

GROUP BY deptno

HAVING count(*)>3;

FROM emp

GROUP BY deptno

HAVING count(*)>3;

When you roll two dice, you have 6 possibilities for each roll (6 sides). This is 36 total combinations.

Let's list the combinations that result in sums greater than 9.

(4,6) (6,4) (5,5) (6,5) (5,6) (6,6)

That's 6 out of the 36 total possibilities. Therefore, the remaining 30/36 possibilities fulfill the less than or equal to 9 requirements. Simplifying by a factor of 6, that's 5/6 chance.

Let's list the combinations that result in sums greater than 9.

(4,6) (6,4) (5,5) (6,5) (5,6) (6,6)

That's 6 out of the 36 total possibilities. Therefore, the remaining 30/36 possibilities fulfill the less than or equal to 9 requirements. Simplifying by a factor of 6, that's 5/6 chance.

Shorter. Regression to the mean

Collaborative Filtering