# Arithmetic Mean

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## Definition of 'Arithmetic Mean'

The arithmetic mean, also called the average, is a measure of central tendency that is calculated by adding the values in a data set and dividing the sum by the number of values. The arithmetic mean is a simple and intuitive measure of central tendency, but it can be misleading if the data set is skewed or has outliers.

To calculate the arithmetic mean, you first need to add all of the values in the data set. Then, you divide the sum by the number of values in the data set. For example, if you have a data set of five values, 1, 2, 3, 4, and 5, the arithmetic mean would be (1 + 2 + 3 + 4 + 5) / 5 = 3.

The arithmetic mean is a useful measure of central tendency because it is easy to calculate and understand. However, it can be misleading if the data set is skewed or has outliers. A skewed data set is one in which the values are not evenly distributed around the mean. For example, a data set of incomes might be skewed if there are a few people who earn very high incomes. Outliers are values that are much larger or smaller than the rest of the data. For example, a data set of test scores might have an outlier if there is one student who scores very low.

If a data set is skewed or has outliers, the arithmetic mean may not be a good representation of the data. In these cases, it may be better to use a different measure of central tendency, such as the median or the mode.

The median is the middle value in a data set when the values are arranged in order from smallest to largest. The mode is the value that occurs most frequently in a data set. Both the median and the mode are less affected by outliers than the arithmetic mean.

The arithmetic mean is a useful measure of central tendency, but it is important to be aware of its limitations. If the data set is skewed or has outliers, the arithmetic mean may not be a good representation of the data. In these cases, it may be better to use a different measure of central tendency, such as the median or the mode.

To calculate the arithmetic mean, you first need to add all of the values in the data set. Then, you divide the sum by the number of values in the data set. For example, if you have a data set of five values, 1, 2, 3, 4, and 5, the arithmetic mean would be (1 + 2 + 3 + 4 + 5) / 5 = 3.

The arithmetic mean is a useful measure of central tendency because it is easy to calculate and understand. However, it can be misleading if the data set is skewed or has outliers. A skewed data set is one in which the values are not evenly distributed around the mean. For example, a data set of incomes might be skewed if there are a few people who earn very high incomes. Outliers are values that are much larger or smaller than the rest of the data. For example, a data set of test scores might have an outlier if there is one student who scores very low.

If a data set is skewed or has outliers, the arithmetic mean may not be a good representation of the data. In these cases, it may be better to use a different measure of central tendency, such as the median or the mode.

The median is the middle value in a data set when the values are arranged in order from smallest to largest. The mode is the value that occurs most frequently in a data set. Both the median and the mode are less affected by outliers than the arithmetic mean.

The arithmetic mean is a useful measure of central tendency, but it is important to be aware of its limitations. If the data set is skewed or has outliers, the arithmetic mean may not be a good representation of the data. In these cases, it may be better to use a different measure of central tendency, such as the median or the mode.

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Copyright © 2004-2023, MyPivots. All rights reserved.