Hi i have seen few videos and read some articles as well but i am still confused, i'll trying quoting the example i saw. Helen sells chocolate nutties which claims to have 70gm or more peanuts in a 200 gm chocolate. Customers complains of chocolate not having enough peanuts.so
Null hypthesis : Chocolate contains >=70gm peanuts Alternate hypothesis : chocolate contains <70 gms peanuts
Helen selects significance level of 0.05%
Helen takes some samples and find out average amount of peanuts in chocolates it comes out to be 68.7 gms
Now she finds out the p-value for this statistical test, it comes out to be - 0.18 =18%
What is stated in video : since the p-value is high, which means there is higher chance (18%, which i higher than significance level) of occurence of what we have observed ( mean to be 68.7 gm), "if null hypothesis is true". So we can not reject the null hypthesis.
Confusion : P-value states if null hypothesis is true, then how likely is to get the results like we have got. If we consider chocolate contains >=70 gm of peanuts as true, and the chances of getting mean of 68.7 gm from the samples is high (18 %) then shouldn't we reject the null hypothesis because if chocolate are having >=70 gm of peanuts then getting chances less peanuts should be very low?? And had we got the p value as 0.01 (1%) the we should accept the null hyothesis as there is very less chance of getting less peanuts..