The smaller the E value, the appropriate Sample size one can yield out of this formula. E is the Margin of Error, which is a % value that tells how much you can wait for your results to reflect the end results or opinions from the overall population. P is nothing but the proportion of the population. Here it has 2 standard deviations above its mean. This Z score tells you the number of standard deviations your data set has above from the mean data point. Assume you have a normally distributed data set of 80, and the mean of the data set is 50 and a standard deviation of 15. X is the population’s total number, M is the population’s mean, and σ is the standard deviation. Generally, you can note this value from the Z table. So Z score is the total number of standard deviations it has before and after that mean data point. That is, say you have a particular population size, which has some mean, a data point. It is the number of the standard deviation a mean data point of a population has. Z value can be called a Z score or Standard Score value. Sample Size = 1.33 / (1 + ((1.33 – 1) / 52))įor this data set, the appropriate Sample size is 1.32 Explanation.For 95 % of the confidence value, the Z value will be 1.96 per the normal table. Calculate Sample Size using the information:Īssuming this is the normal distribution, let us find the Z value from the Z table. The Confidence level is 95%, and the Margin of Error also consider as 85%. Half of the hotels may render breakfast service for the customers hence let us take P as 0.5. We need to find how many hotels provide breakfast in X.
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