Normal Distribution

Central Limit Theorem: Theorem which stats as the sample size increases, the sampling distribution of the sample means will become approximately normally distributed.
Correction for Continuity: A correction applied to convert a discrete distribution to a continuous distribution.
Finite Population Correction Factor: A correction applied to the standard error of the means when the sample size is more than 5% of the population size and the sampling is done without replacement.
Sampling Distribution of the Sample Means: Distribution obtained by using the means computed from random samples of a specific size.
Sampling Error: Difference which occurs between the sample statistic and the population parameter due to the fact that the sample isn't a perfect representation of the population.
Standard Error or the Mean: The standard deviation of the sampling distribution of the sample means. It is equal to the standard deviation of the population divided by the square root of the sample size.
Standard Normal Distribution: A normal distribution in which the mean is 0 and the standard deviation is 1. It is denoted by z.
Z-score: Also known as z-value. A standardized score in which the mean is zero and the standard deviation is 1. The Z score is used to represent the standard normal distribution.