Z = (mean1 - mean2)/standard error (SE) of difference between means
SEdiff = √(SEmean1^2 + SEmean2^2)
SEm = SD/√n
If only one SD is provided, you can use just that to determine SEdiff.
Find table in the back of your statistics text labeled something like "areas under normal distribution" to find the proportion/probability related to the Z score.
A sample of 100 iron bars is said to be drawn from a large number of bars.
Whose lengths are normally distributed with mean 4 feet and S.D 0.6ft. If the
sample mean is 4.2 ft, can the sample be regarded as a truly random sample?
2 answers
A sample of 100 iron bars is said to be drawn from a large number of bars.
Whose lengths are normally distributed with mean 4 feet and S.D 0.6ft. If the
sample mean is 4.2 ft, can the sample be regarded as a truly random sample?
Whose lengths are normally distributed with mean 4 feet and S.D 0.6ft. If the
sample mean is 4.2 ft, can the sample be regarded as a truly random sample?
1 answer