So here we have a Z score that now falls To the right of my population mean of zero. Now let's just come up with an arbitrary number again. So we'll say Z here equals 1.82 for that value. So remember the first two digits from my Z score are found here in this column. So we have to look for 1.8 And then the third digit, the two we look here at .02, we'd see where they would meet up. So they'd meet up here. That means that my probability p equals .9656. So that would mean times 196.56%. So that means here that if we're taking a consideration all the negative portion of my Gaussian distribution curve plus this portion up to Z. That would represent 96.56% of my entire population. Now besides that, what if they were to ask me um what is the probability if we're looking at Z equals zero to Z equals 1.82. In that case we'd only be looking at this portion of my Gaussian distribution curve. Okay, so we'd only be looking at this portion here. Now remember the mean represents the exact center of my Gaussian distribution curve? That would mean that this portion here represents 50 And then the other half represents 50%. So we're not looking at the 50%, the part that's the left of my population mean. So all we have to do to figure out what's the percentage between these two Z values is just do 96.56% -50%. And that would give me 46.56% of the population would fall between a Z score of 0 to Z score of 1.82. So again, just remember, in order to determine the probability of a population falling within certain parameters, we have to find our Z. Score and then compare it to our Z. Table in order to find our value P, which represents the probability the percentage that we're looking for.