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AI•Statistics

Descriptive Statistics

Descriptive Statistics is broken down into Tendency and Variability .

Tendency is about Center Measures

  • The Mean (the average value)
  • The Median (the mid point value)
  • The Mode (the most common value)

The Mean

The Mean Value is the Average of all values.

This table contains 11 values

7889991011141415

To find the Mean Value : Add all values and divide by the number of values.

The Mean Value is: (7+8+8+9+9+9+10+11+14+14+15)/11 = 10.3636363636.

The Mean is the Sum divided by the Count .

Runnable example

let mean = (7+8+8+9+9+9+10+11+14+14+15)/11;

Runnable example

const values = [7,8,8,9,9,9,10,11,14,14,15];
let mean = math.mean(values);

The Median

A list of speed values

99,86,87,88,111,86,103,87,94,78,77,85,86

The Median is the value in the middle (after the values are sorted):

77,78,85,86,86,86, 87 ,87,88,94,99,103,111

Runnable example

const speed = [99,86,87,88,111,86,103,87,94,78,77,85,86];
let median = math.median(speed);

If there are two numbers in the middle, divide the sum of them by two.

77,78,85,86,86, 86,87 ,87,88,94,99,103
(86 + 87) / 2 = 86.5

Runnable example

const speed = [99,86,87,88,86,103,87,94,78,77,85,86];
let median = math.median(speed);

The Mode

The Mode Value is the value that appears the most number of times:

99, 86 ,87,88,111, 86 ,103,87,94,78,77,85, 86

Runnable example

const speed = [99,86,87,88,86,103,87,94,78,77,85,86];
let mode = math.mode(speed);

Outliers

Outliers are values " outside " the other values:

99,86,87,88,111,86,103,87,94,78, 300 ,85,86

Outliers can change the mean a lot. Sometimes we don't use them (they might be an error), or we use the median or the mode instead.

Runnable example

const values = [99,86,87,88,111,86,103,87,94,78,300,85,86];
let mean = math.mean(values);

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Machine Learning Statistics

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Statistic Variability (Spread)

This chapter

Overview
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1. Machine Learning Statistics2. Descriptive Statistics3. Statistic Variability (Spread)4. Distribution5. Probability

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The MeanThe MedianThe ModeOutliers