Hi Joseph Ozigis Akomodi

Mean, median, and mode are important in data analysis because they help summarise large datasets with single representative values. They provide insights into the central tendency of the data, making it easier to understand patterns, compare groups, and support decision-making.

I hope that helps.

Regards,

Dr. Samer Sarsam

Mean presented with SD standard deviation if parametric normal distribution to represent to population ( if small sample size > 50 generally) according to one of 4 random sampling techinues.

While median presented with IQR interquartile range if non-paramteric distribution if small sample size < 50 generally according to non-random sampling techinues.

references said about sample size as a cut off points :

n = 25

n = 30

n = 50

n = 60

Mode has no improtance in statistical tables in results`s chapter.

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In Six sigma we use those 3 measures if representative values by deviding one of them on the other.

for example :

mean/median = 95%

median /mode = 95%

mean/ mode = 95%

according to my school in IQF.

Mean, median, and mode are fundamental measures of central tendency used to summarize and understand datasets in data analysis. The mean is the average of all values and provides a general overview, but it can be skewed by extreme values. The median is the middle value when data is ordered and is useful when the data is skewed or contains outliers, as it better represents the typical value. The mode is the most frequently occurring value and is especially helpful for analyzing categorical data or identifying common patterns. Together, these measures help describe the center of a dataset, reveal distribution characteristics, and guide the selection of appropriate analytical methods.

Mean, median, and mode are vital in summarizing datasets by providing measures of central tendency; the mean gives an average, the median shows the middle value, and the mode reflects the most common response, each useful depending on the data type and distribution.