Why is measure of dispersion important

Example : Find the median absolute deviation of climatological monthly precipitation in South America for January to December Select the "Datasets by Catagory" link in the blue banner on the Data Library page.

CHECK The above command computes the median value over the monthly climatologies at each grid point in the field. Enter the command: [T] medianover Click the OK button. Similar to the IQR example, the Amazon Basin exhibits high intraannual precipitation variability, while areas to the north and south exhibit lower precipitation variability.

Trimmed Variance Similar to variance, except that a proportion of the largest and smallest values in the dataset are ommitted before it is calculated. Sometimes multiplied by an adjustment factor to make it more consistant with the ordinary sample variance. Wilks, Daniel S. Statisical Methods in the Atmospheric Sciences. Analogous to the trimmed mean. Click on the "Cloud Characteristics and Radiation Budget" link. Click on the "monthly" link Select the "outgoing longwave radiation" link under the Datasets and Variables subheading.

Select the Average over "XY" link. The result is located under the Expert Mode text box in bold: Make a note of this value. In the source bar, click on the [X Y] average box.

This operation undoes the replacebypercentile command. Return to Expert Mode. Enter the following command under the text already there: [T]. The result should be Click on the "Filters" link in the function bar. The value of the root mean square is 7. Calculate the trimmed variance by squaring the value above. To see the results of this operation, choose the viewer window with land drawn in black. Maximum Observed Sea Surface Temperatures. For more help in Significance of Measuring Dispersion click the button below to submit your homework assignment.

Submit Assignment Now! Your Registration is Successful. Please login and proceed with profile update. Got it!! It is usually used in conjunction with a measure of central tendency , such as the mean or median, to provide an overall description of a set of data.

There are many reasons why the measure of the spread of data values is important, but one of the main reasons regards its relationship with measures of central tendency. A measure of spread gives us an idea of how well the mean, for example, represents the data.

If the spread of values in the data set is large, the mean is not as representative of the data as if the spread of data is small.

This is because a large spread indicates that there are probably large differences between individual scores. Additionally, in research, it is often seen as positive if there is little variation in each data group as it indicates that the similar. We will be looking at the range, quartiles, variance , absolute deviation and standard deviation. The range is the difference between the highest and lowest scores in a data set and is the simplest measure of spread. The way we perceive the variability gives us information on the dispersion, or spread of the data, in terms of a mean or a median.

A mean, or an average, is very common in statistics. There are three important components in measures of dispersion that are related to random variability 2 :. They can also help you figure out if your data is far from its central tendency. This is very helpful when it comes to comparing distributions and understanding the risks of making certain decisions 1. To sum up, the greater the dispersion, the less representative your central tendency is. Here are the most common measures of dispersion:.

Range is generally best for making your first comparisons because it only looks at the two extremes of your data. The basic definition of range is: the difference between the first and last data.