standard deviation — OpenTuition Forums

((deleted)5y ago

hi please could you explain what standard deviation and what it has to do with a table and graph. Can you please explain the following question in the acca mock The results of a chemistry examination are normally distributed with a mean score of 56 and a standard deviation of 12. What is the percentage probability that a student will score more than 80? thanks in advance

John MoffatTutor5y ago#1

I explain all of this in my free lectures on Chapters 23 of our free lecture notes. Please watch the lectures and you should then find this question very easy. (If not then obviously ask again :-) )

Eeh5y ago#2

hi thanks for your reply... but i did watch your lecture and didnt understand so please can you explain in writing? thanks

John MoffatTutor5y ago#3

We know that there is a 50% chance of being more than the mean of 56. We can find the probability of being between the mean and 80, but looking it up from the tables for a z score of (80 - 56) / 12 = 2.00 The probability of being more than 80 is 50% less the figure from the tables.

Eeh5y ago#4

thanks for that but what does that have to do with a graph as i see in your lecture?

John MoffatTutor5y ago#5

If you watch the lecture carefully you will see that a quick sketch graph is useful in sorting out what is being asked for. Obviously you cannot be asked to draw a graph in the exam, it is only a quick sketch anyway, and if the situation is immediately obvious from the question then you don't need to do it anyway.

Eeh5y ago#6

thanks.. can you please explain the multiple formulas to standard deviation???? thanks

John MoffatTutor5y ago#7

Multiple formulas are not needed for the exam. The only formulae you need are those that I show in my lecture.

Eeh5y ago#8

thanks.... just one more thing.... what does standard deviation have to do with variance and get a standard deviation by rooting the variance? thanks in advance

John MoffatTutor5y ago#9

The variance is a measure of spread. The standard deviation is the square root of the variance - we take the square root so as for it to be in the same units as the original distribution. I do explain this in my free lectures.