INTELLIPATH - MATH 301 INTELLIPATH Z DISTRIBUTION...

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MATH 301 INTELLIPATH Z DISTRIBUTION Introduction As it was previously mentioned, we use Z-distribution for the samples drawn from a normally distributed population or with samples of size greater or equal to thirty even though we know the population they have been drawn from is not perfectly normally distributed. We present the equations to calculate the z-scores as well as the limits for the confidence interval. Learning Material Z-distribution can be used to calculate the confidence interval for sampling distribution drawn from normally distributed population of samples of size thirty or more drawn from a population which is not normally distributed. Z-distribution is very much resembles standard normally distribution. Its mean value is zero with a standard deviation of one. If we use only a sample in our experiment, the z-score can be calculated by: However, if sampling distribution is used involving many samples, the z-score can be calculated by: The confidence interval is constructed by the following equation: where margin of error depends on the critical value, standard deviation of the

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