The human life cycle is a classic example of asymmetrically distributed data. The mean of such data is generally greater than the other measures of central tendency of data such as median or mode. This is because a large percentage of the total people residing in a particular state tends to fall under the category of a low-income earning group, while only a few people fall under the high-income earning group. Income distribution is a prominent example of positively skewed distribution. Similarly, the distribution of scores obtained on an easy test is negatively skewed in nature because the reduced difficulty level of the exam helps more students score high, and only a few of them tend to score low. This is because due to the increased difficulty level of the exam, a majority of students tend to score low, and only a few of them manage to score high. The distribution of scores obtained by the students of a class on any particularly difficult exam is generally positively skewed in nature. The representation of exam results forms a classic example of skewed distribution in real life. Similarly, a positively skewed distribution can be used if most of the players of a particular team score badly during a match, and only a few of them tend to perform well. In such a case, the data is generally represented with the help of a negatively skewed distribution. Let us say that during a match, most of the players of a particular team scored runs above 50, and only a few of them scored below 10. Cricket ScoreĬricket score is one of the best examples of skewed distribution. The mean of the distribution can be zero or negative and has less magnitude as compared to the median and mode.Įxamples of Skewed Distribution 1. More values are plotted on the right side of the distribution, and only a few of them are present on the left or the tail side. If a distribution has a tail on the left side, it is said to be negatively skewed or left-skewed distribution. The mean of the distribution has a positive value and is present on the right side of the median and mode of the data. More values are plotted on the left side of the distribution, and only a few of them are present on the right or the tail side. If a distribution has a tail on the right side, it is said to be positively skewed or right-skewed distribution.
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