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When p-value is equal to Alpha?
If the p-value is less than or equal to the alpha (p< . 05), then we reject the null hypothesis, and we say the result is statistically significant. If the p-value is greater than alpha (p > . 05), then we fail to reject the null hypothesis, and we say that the result is statistically nonsignificant (n.s.).
What does p equal in binomial distribution?
A Binomial Distribution shows either (S)uccess or (F)ailure. The first variable in the binomial formula, n, stands for the number of times the experiment runs. The second variable, p, represents the probability of one specific outcome.
What if p-value is equal to significance level?
If p value equals to 0.05 we should reject the null hypothesis. The significance level “alpha” is defined as the risk of rejecting a true null hypothesis H0 (risk of type 1 error, or false positive). The p-value is defined as the probability of getting a test statistic at least as extreme as observed, under H0.
What happens when the p value is greater than the Alpha?
If the p-value is less than or equal to the alpha (p<.05), then we reject the null hypothesis, and we say the result is statistically significant. If the p-value is greater than alpha (p >.05), then we fail to reject the null hypothesis, and we say that the result is statistically nonsignificant (n.s.).
Which is an example of normal approximation of a binomial distribution?
P ( X = 0) + P ( X = 1) + P ( X = 2) + P ( X = 3) + P ( X = 4) + P ( X = 5). The use of the binomial formula for each of these six probabilities shows us that the probability is 2.0695%. We will now see how close our normal approximation will be to this value. Checking the conditions, we see that both np and np (1 – p) are equal to 10.
When to use the normal approximation of NP?
In order to use the normal approximation, we consider both np and n( 1 – p ). If both of these numbers are greater than or equal to 10, then we are justified in using the normal approximation. This is a general rule of thumb, and typically the larger the values of np and n( 1 – p ), the better is the approximation.
Which is an example of a normal approximation?
The use of the binomial formula for each of these six probabilities shows us that the probability is 2.0695%. We will now see how close our normal approximation will be to this value. Checking the conditions, we see that both np and np (1 – p) are equal to 10. This shows that we can use the normal approximation in this case.