Measures of Center (Mode, Median, Mean) | Statistics Tutorial 001
Subscribe to RichardOnData here: / @richardondata
Welcome to my Data Science Statistics Tutorial series! I go over concepts from statistics that you're likely to use in a practical manner in an applied data science role.
The three key measures of center in a variable are: the mean, the median, and the mode. However, they can differ from each other radically and tell completely different stories.
The MODE is the number which occurs the most frequently. It is by far the least used of these measures because it's not usually very informative and doesn't have helpful mathematical properties. The MEDIAN, or 50th percentile, is the "middle" number of the data, representing that value which approximately half of the data are less than and half of the data are more than. The MEAN, also known as the expected value of the variable, is equal to the sum of the data over the number of data points.
The mean is very sensitive to outliers while the median is not. This can lead to vastly different values between these two numbers, and prompts some natural questions. Why are there outliers? Are those data points accurate or problems with the actual data? Which one provides the most accurate description of the data?
#Statistics #DataScience #StatisticsForDataScience
PayPal: [email protected]
Patreon: / richardondata
BTC: 3LM5d1vibhp1F7pcxAFX8Ys1DM6XLUoNVL
ETH: 0x3CfC599C4c1040963B644780a0E62d45999bE9D8
LTC: MH8yPjvSmKvpmRRmufofjRB9hnRAFHfx32