Negatively Skewed Distribution Definition Examples Interpretation

Negatively Skewed Distribution Definition

Explanation

The distributions have a wide gap as the negative side is heavy. For example, the data contains income distribution. The income of the rich class is much higher than the lower and middle class, so there is a wide gap in the income distribution which means it will be above average due to the high gap. In a negatively skewed distribution, the left tail is longer in the graph. It shows unfavorable conditions for any nation, which means there is vast inequality in the distribution of income, which might result in the underdevelopment of the nation at large. Poverty, unemployment, etc., increase. In such a situation, the poor get poorer, and the richer get richer.

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Negatively Skewed Distribution Examples

As shown in the above example, there is a wide gap in the income distribution, and the tail is bent more toward the left side of the plotting area, which reflects the distribution is negatively skewed.

Mean = (Sum of all the Number in the Data) / n

Where n is the number of samples

=$ 3,000 + 4,000+5,000 + 7,000 + 7,500+8,500 + 23,000 / 7= $ 58,000/7= $ 8,585 (Appx)

Median Value = (n+1)/2 Value

= (7 + 1 / 2) Value= 4th Value= $ 8,000

Mode = Highest Value = $ 35000

Real-Life Examples of Negatively Skewed Distribution

In cricket, some players scored lower than the average. Some get out on zero, some score very low runs, and only one or two players make the highest scores, which might result in the team’s winning. Still, the distribution is negatively skewed if we see the scores player-wise.Another example is university exams. The exams are the same, but a few scoreless, a few score average, and a few scores a high percentage, which shows the data are negatively skewed.In the USA, most people belong to the average income group, and very few belong to the high-income group. Therefore, it shows there is an unequal distribution of income. Hence, the data is negatively skewed.The human life cycle is also an example of negatively skewed distribution as many live the average life, some live very less, and some live a very high life in age.The taxation regime of underdeveloped countries and developing countries also show this type of distribution as most people pay the average or low-income tax. In contrast, only a few people pay very high-income taxes. It is due to the unequal distribution of income and wealth.

Interpretation

It shows that there is a wide gap between the earnings.It shows the underdevelopment of the economy.It reflects the poor population of the country.It shows the failure of governmental measures on the distribution of income.It shows a fault in governmental policies.It reflects the slow growth of the country.It reflects the exploitation of labor or the availability of cheap labor. Hence, the government must take measures to provide rights to the laborers.It shows the volatile nature of the market.It is a sign of weak domestic currency.It reflects the losses to the investors hence discouragement of the investment.

Central Tendency of Negatively Skewed Distribution

Central tendency refers to the distribution’s meanMeanMean refers to the mathematical average calculated for two or more values. There are primarily two ways: arithmetic mean, where all the numbers are added and divided by their weight, and in geometric mean, we multiply the numbers together, take the Nth root and subtract it with one.read more, medianMedianThe median formula in statistics is used to determine the middle number in a data set that is arranged in ascending order. Median ={(n+1)/2}thread more, and mode. In the case of the normally skewed data, the mean, median, and mode are equal, which shows the equal distribution of income and wealth and the positive role of government efforts and the development of the economy.

In a positively skewed distributionPositively Skewed DistributionA positively skewed distribution is one in which the mean, median, and mode are all positive rather than negative or zero. The data distribution is more concentrated on one side of the scale, with a long tail on the right.read more,the country has favorable conditions as a large population belongs to the same group, and very few populations differ from the crowd. In a positively skewed distribution, mean, median, and mode are positives. In this case, the mean is greater than the median, and the median is greater than the mode.

Whereas in negatively skewed distribution, data shows the unequal distribution, the central tendency shows as under:

Mode > Median > Mean.

The median is the middle value, and the mode is the highest. But, due to unequal distribution, the median will be higher than the mean.

Negatively Skewed Distribution in Finance

In finance, skewed distribution is used to evaluate the return on the investment. Therefore, negatively skewed data signifies a lower return on investment. Hence, the investor finds it risky to invest in countries where the income is negatively skewed due to long-term losses and currency fluctuation in the international market. However, those investors who look for short-term benefits can invest in negatively skewed distributed countries.