The mean of a proportion, p, is X/n; where X is the number of instances & n is the sample size; and its standard deviation is sqrt[p(1-p)]
The standard deviation is sqrt[n*p*(1-p)] = sqrt(1000*0.94*0.06) = 7.51 approx.
You can't. You need an estimate of p (p-hat) q-hat = 1 - p-hat variance = square of std dev sample size n= p-hat * q-hat/variance yes you can- it would be the confidence interval X standard deviation / margin of error then square the whole thing
Let M be the mean. P( X > 5.52) =0.1271 Standardize X by subtracting the mean and dividing by the standard deviation. z = (52.2-M) /4 From the normal distribution tables, P( z > 1.14 )=0.1271 Therefore, (52.2-M) / 4 = 1.14 Solve for M, the mean. 52.2-M = 4(1.14) = 4.56 M=52.2-4.56 =47.64
Yes. The normal distribution is used to approximate a binomial distribution when the sample size (n) times the probability of success (p), and the probability of failure (q) are both greater than or equal to 5. The mean of the normal approximation is n*p and the standard deviation is the square root of n*p*q.
The mean of a proportion, p, is X/n; where X is the number of instances & n is the sample size; and its standard deviation is sqrt[p(1-p)]
The standard deviation is sqrt[n*p*(1-p)] = sqrt(1000*0.94*0.06) = 7.51 approx.
0.84
Note that if the first one is multiplied by 2, you get 200*2=400 and 120*2=240. The 240 is the same as in the second test, but the population size is smaller, so the second is less. To test the significance of this difference, you would take 500-400 and divide by some standard deviation. One way to approximate this standard deviation is to say that it is from a binomial distribution with p = the average of 120/200 and 240/500. The standard deviation is sqrt[(average number of people)p(1-p)]. Use this and calculate how many standard deviations there are between the two. Look up this value on the normal distribution table to determine what will be the probability of being differernt.
For a binomial probability distribution, the variance is n*p*q which is 80*.3*.7 = 16.8. The standard deviation is square root of the variance which is 4.099; rounded is 4.1. The mean for a binomial probability distribution is n*p or 80*.3 or 24.
n = 736, p = 0.7 So variance = 736*0.7*(1-0.7) = 154.56 and therefore standard deviations = sqrt(154.56) = 12.43
You can't. You need an estimate of p (p-hat) q-hat = 1 - p-hat variance = square of std dev sample size n= p-hat * q-hat/variance yes you can- it would be the confidence interval X standard deviation / margin of error then square the whole thing
It is sqrt[(1-p)/p2] = 0.666... recurring.
There is not enough information to find n & p. The mean is n*p and the std dev = sqrt (n*p*q). You have to be given n, p or q to have 2 equations 2 unknowns to solve.
Cpk = Cp (Process Capability) + p (katayori) Japanese for deviation. Cpk = Deviation of process capability
P. K. Sarangapani died on 2011-02-02.
μ = 10.5 σ = 0.3 P(x > 10.95) = P( z > (10.95-10.5) / 0.3) = P(z > 1.5) = 0.0668 or 668/1000 (using Normal probability table)