I’m taking a statistics course in school now, and we’ve just done z-scores. My question is simple: given a certain z-score, how do I calculate the percentage of the results (in a normal distribution) between that score and the mean (score 0). We were given a table of these values for successive z-scores, but it’s rather cumbersome to use.
I can’t find anything on Google about this, only more tables like the one I got and programs that reference a table internally.
Are you sure? Because when I googled for Gaussian distribution to make sure I wasn’t giving you bad advice the first link had an explanation of the function.
I’m still in high school, taking “Honors PreCalculus”, which is delving into statistics for the next month. It’s rather hard for me to understand the link you supplied.
Basically, I want a way of getting the following sort of information without using a table: given a normal distribution, 34% of the data points will fall within one standard deviation of the mean. 47.5% of the data points will fall within two standard deviations of the mean. Etc.
If this can’t be done without using operations my TI-89 can do (or ones that I can learn within a reasonable amount of time), I guess I’ll stick with my tables until I get to college.
The problem is, the percentage within n standard deviations of the mean in a normal distribution can’t be calculated using any functions you’d be comfortable with. The tables are your onl realistic option at this point. Sorry.
I don’t know of any other way than using the tables, other than using numerical integration, which is going to be vastly more laborious. That’s why there are published tables, because there’s no quicker way.
My calculator can do integration - it is something that I could just tell it to do and not need to know the workings, or does it require more than finding the integral of one function?
And if I obviously don’t know what I’m talking about, sorry :). I don’t.
If you’re clever, you can do it. You may run into trouble as the necessary integrals may be improper, but if you’re clever, you can get around that.
Here are some facts that’ll help you be clever. Let C(x) denote the probability that a N(0, 1) (that’s a normal distribution with mean 0 and variance 1) variable is less than or equal to x.
where Sqrt( is your square root button there, and pi is your constant pi. I think this will work, but it’s been a couple of years since I’ve worked with that calculator. If I got the notation right, you should be able to input stuff like Y[sub]1/sub and get stuff like 0.8413447. Is that even right?
Oh oops. I see that you wanted the percentage between the given z-score and the mean, not negative infinity. The only necessary change to the function I gave is remove the 0.5+ from the beginning.
You can also do it using power series. Multiply 1 over the square root of 2 * pi by the sum of
(-1)^n * [1/(2n+1)] * [1/2^n] * [1/n!] * z^(2n+1)
starting with n = 0 and going to infinity—or until you get two successive running totals (“partial sums”) that agree to within the degree of accuracy you want.
Come back after you’ve had a couple of semesters of calculus and I can explain how I got this formula.