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To obtain a much better, simpler, and more practical understanding of the data distribution.

Q: Why do we have to compute for the mean median mode and standard deviation?

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In the same way that you calculate mean and median that are greater than the standard deviation!

msd 0.560

characteristics of mean

mean | 32 median | 32 standard deviation | 4.472 ========================================================================

mean

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In the same way that you calculate mean and median that are greater than the standard deviation!

msd 0.560

characteristics of mean

The mean, median, and mode of a normal distribution are equal; in this case, 22. The standard deviation has no bearing on this question.

Mean: 26.33 Median: 29.5 Mode: 10, 35 Standard Deviation: 14.1515 Standard Error: 5.7773

mean | 32 median | 32 standard deviation | 4.472 ========================================================================

The mean deviation from the median is equal to the mean minus the median.

The coefficient of skewness is a measure of asymmetry in a statistical distribution. It indicates whether the data is skewed to the left, right, or is symmetric. The formula for calculating the coefficient of skewness is [(Mean - Mode) / Standard Deviation]. A positive value indicates right skew, a negative value indicates left skew, and a value of zero indicates a symmetric distribution.

The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.

mean

mean | 30 median | 18 standard deviation | 35.496

You don't need to. The mean deviation is, by definition, zero.