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Measures of Dispersion- Standard deviation, Mean deviation, Variance

Measures of Dispersion are an important topic when it comes to the subject of statistics. The Measures of Dispersion in statistics are standard deviation, mean deviation and variance. Dispersion in simple terms means scattering. This is exactly what Measures of Dispersion studies. We study the scattering of values from its standards to know the amount of deviation that there is.

Some important notes for Measures of Dispersion

1. Standard deviation is the value which represents how much the data or results differs from the mean (average) of the whole data. In other words, it calculates the dispersion of data from the mean value.

2. Mean deviation is similar and calculates the absolute deviation of the whole data to the mean of the data.

3. Variance is just a measure to show how much difference does the standard deviation or the mean deviation has regarding the mean of the product.

4. The measure of dispersion are a value of how much change is there and are not the actual values. For, e.g., if the standard deviation 2, it means that the data and the mean of the data differ by 2%.

5. In order to calculate standard deviation, mean deviation and variance, one first needs to know how to calculate mean which is the base of all these dispersion measures.

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When it comes down to solving the problems and assignments of Measures of Dispersion problems, there are complex calculations involved in every step. The numbers usually end up in decimal points which add to the level of complexity.

There are lots of formulas which are involved which make solving these problems extremely challenging. The formulas involve complicated mathematical calculations like square root, multiplications, divisions etc. To add to this, the data that is given in problems tend to be huge which makes one problem take about an hour at times to complete. With one mistake, the whole problems need to be done again.

Students face issues with solving these problems as it requires time, concentration and mathematical skills. It requires focus and takes up a lot of energy.

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