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#1
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Hi

I dont understand Binomial distrubution, normal distrubution, confidence intervals

The formulas are so confusing especially when they do root of n
root of n-1
standard devation..

For confidence intervals i only know the formula of M +- Z standard deviation over Root of n
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Can someone sum it up for me with all formulas thanks
also i like to use the tables in the back of the formula book to find the values
i cant do inverse norm either
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(Original post by sue99)
I can try and help you understand the binomial and normal distributions. Confidence intervals aren't part of my Maths spec so I can't help you there.
What is puzzling you about the binomial and normal distributions?
basically i know how to find the values in the back of the book more than less than
and for exactly you need to use the nCr buttons i think
for confidence interval isnt there loads of formulas involved including estimation and standard errors
when it asks for random samples and stuff centeral limit theorem dont rly know any of this im confused on which formula to use for what wording
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bump.
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sue99
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(Original post by sadsadsadsad)
basically i know how to find the values in the back of the book more than less than
and for exactly you need to use the nCr buttons i think
for confidence interval isnt there loads of formulas involved including estimation and standard errors
when it asks for random samples and stuff centeral limit theorem dont rly know any of this im confused on which formula to use for what wording
so, when you have a random sample, we normally assume that it is a normal distribution
you can go from binomial to normal or poisson to normal

binomial is a discrete distribution and normal is a continuous distribution so you have to employ a continuity correction when you're going from binomial to normal
- when you're going from binomial to normal, there are also certain conditions that have to be fulfilled first, ie. np>5 and nq>5
- when you're going from binomial to a normally distributed RANDOM SAMPLE , the value of X is + or - 1/(2n) depending on what the question is asking you

poisson is also a discrete distribution so the above applies, except for the fact that lamda must be greater than 15

when going from a normal distribution to a normally distributed random sample, you employ the Central Limit Theorem, on the condition that n>30
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sue99
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sometimes in exams, you may be asked whether it was necessary to employ the CLT
here, if you know the parent distribution, CLT is not required, but if the parent distribution is not known, CLT should be employed

If there is something you do not understand here, please do not hesitate to ask me

(Original post by sue99)
so, when you have a random sample, we normally assume that it is a normal distribution
you can go from binomial to normal or poisson to normal

binomial is a discrete distribution and normal is a continuous distribution so you have to employ a continuity correction when you're going from binomial to normal
- when you're going from binomial to normal, there are also certain conditions that have to be fulfilled first, ie. np>5 and nq>5
- when you're going from binomial to a normally distributed RANDOM SAMPLE , the value of X is + or - 1/(2n) depending on what the question is asking you

poisson is also a discrete distribution so the above applies, except for the fact that lamda must be greater than 15

when going from a normal distribution to a normally distributed random sample, you employ the Central Limit Theorem, on the condition that n>30
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(Original post by sue99)
so, when you have a random sample, we normally assume that it is a normal distribution
you can go from binomial to normal or poisson to normal

binomial is a discrete distribution and normal is a continuous distribution so you have to employ a continuity correction when you're going from binomial to normal
- when you're going from binomial to normal, there are also certain conditions that have to be fulfilled first, ie. np>5 and nq>5
- when you're going from binomial to a normally distributed RANDOM SAMPLE , the value of X is + or - 1/(2n) depending on what the question is asking you

poisson is also a discrete distribution so the above applies, except for the fact that lamda must be greater than 15

when going from a normal distribution to a normally distributed random sample, you employ the Central Limit Theorem, on the condition that n>30

In a normal distrubution when it gives you the Z values the standard deviation and n how do you calculate the Mean do u do inverse norm or something
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sue99
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(Original post by sadsadsadsad)
In a normal distrubution when it gives you the Z values the standard deviation and n how do you calculate the Mean do u do inverse norm or something
the way to calculate Z for a random sampleis using the formula:

Z = (X - mu)/(sd/root n)

you just multiply Z by sd/root n and take that away from the value of X
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