The p-value which is also referred as calculated probability is the probability through which finding of the observed or extreme cases is possible. Results when it shows null hypothesis, then the question might be true. The ‘extreme’ of finding will depend on a procedure of testing. P can also be defined as rejecting H0 which is true, but not a direct probability.

The statistical significance

In order to understand the outcome in a significant way, it is necessary to compare different value of alpha and p-value. There are two different possibilities that can be observed:

1. The p-value can be either less or equal to alpha. In such case the null hypothesis is rejected. When such occurrences take place, the result appears to be statistically significant. You can say that there a chance that can offer observed sample.

2. If the p-value is greater compared to alpha, then in such a case the null hypothesis is not rejected. Once this happens, then we cannot refer to as statistically significant. Therefore, the observed data can get an explanation by chance.

Examples to support statement

In case a pizza shop claims that their delivery time is 30 minutes or less or average. But, according to you it can be more than what the company says. Therefore, you plan to conduct hypothesis test as you believe in null hypothesis with is H0 this means that the mean delivery time would be max. 30 minutes this is incorrect. A alternative hypothesis (Ha) refers that mean time would be more than 30 minutes. You should also be aware of Does sneezing kill brain cells? This can give knowledge on science.

Random samples of delivery times collected can perform hypothesis test and if p-value turns out to be 0.001 it means that data is less than 0.05. So, there is minimal chance of failing the delivery of pizza within 30 minutes.


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