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The center is the median and/or mean of the data. The spread is the range of the data. And, the shape describes the type of graph. The four ways to describe shape are whether it is symmetric, how many peaks it has, if it is skewed to the left or right, and whether it is uniform.
The spread in data is the measure of how far the numbers in a data set are away from the mean or the median. The spread in data can show us how much variation there is in the values of the data set. It is useful for identifying if the values in the data set are relatively close together or spread apart.
Measures of spread describe how similar or varied the set of observed values are for a particular variable (data item). Measures of spread include the range, quartiles and the interquartile range, variance and standard deviation.
Why is it important to measure the spread of data? 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.
Three main measures of dispersion for a data set are the range, the variance, and the standard deviation.
The center is the median and/or mean of the data. The spread is the range of the data. And, the shape describes the type of graph. The four ways to describe shape are whether it is symmetric, how many peaks it has, if it is skewed to the left or right, and whether it is uniform.
Look at a graph, or a list of the numbers, and see if the center is obvious. Find the mean, the average of the data set. Find the median, the middle number.
There are three methods you can use to find the spread in a data set: range, interquartile range, and variance. Range is the difference between the highest and lowest values in a data set. You can find the range by taking the smallest number in the data set and the largest number in the data set and subtracting them.
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