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Student Project | Nursing | India | Volume 12 Issue 12, December 2023 | Rating: 5 / 10
Normal Distribution
Mahuya Maity | Papiya Saha
Abstract: The primary purpose of this paper is to discuss the idea of normal distribution. The authors describe the definition, formula properties and applications of normal distribution. Normal distribution, also known as the Gaussian distribution, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In graphical form, the normal distribution appears as a "bell curve". That means, the standard normal distribution has two parameters: The mean and the standard deviation (1).This article focuses on properties, formula and its application in nursing research. The normal distribution is one type of symmetrical distribution. Symmetrical distributions occur when where a dividing line produces two mirror images. Not all symmetrical distributions are normal since some data could appear as two humps or a series of hills in addition to the bell curve that indicates a normal distribution. For all normal distributions, 68.2% of the observations will appear within plus or minus one standard deviation of the mean; 95.4% of the observations will fall within +/- two standard deviations; and 99.7% within +/- three standard deviations. This fact is sometimes referred to as the "empirical rule," a heuristic that describes where most of the data in a normal distribution will appear. This means that data falling outside of three standard deviations ("3- sigma") would signify rare occurrences.
Keywords: Symmetrical distribution, mean, standard deviation, bell curve
Edition: Volume 12 Issue 12, December 2023,
Pages: 298 - 299