Standard deviation = √() *The standard deviation of a sample is symboled by s, while the standard deviation of an entire population is symbolized by δ (lowercase sigma). Measures of central tendency do not indicate how items are spread out on either side of the peak/center/mean of the distribution curve and this is the key reason for scholars to use the measures. This value is the standard deviation for the data set. A statistical measuring the spread or variability of the sample around the mean or in other words it may be defined as the measure of dispersion of different. Examples of measures of dispersion include the range, interquartile range, and standard deviation. Measures of dispersion, on the other hand, are statistics that describe how spread out the data in a data set is. Take the square root of the quotient in step 5. Examples of measures of central tendency include the mean, median, and mode. Divide the sum in step 4 by n-1, where n represents the number od data items: / (n-1) 6. Sum the squared deviations: ∑(data item - mean)^2 5. It is simply the total spread in the data, calculated by subtracting the smallest number in the group from the largest number. This is not enough, and well discuss several statistics used to measure. Range is the simplest measure of dispersion. Square each deviation: (data item - mean)^2 4. it refers to the standard deviation as the most commonly used measure of dispersion. Find the deviation of each data item from the mean: data item - mean 3. The standard deviation is found by determining how much each data item differs from the mean.
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