# Mean, Median, and Mode

### Understanding Mean, Median, and Mode in Statistics

If you’re delving into the realm of data analysis and statistics, you’ll inevitably encounter three fundamental concepts: Mean, Median, and Mode. These statistical measures provide valuable insights into data distribution and central tendency. In this expert guide, we’ll demystify these concepts and illustrate them with Python examples to deepen your understanding.

## 1. Mean

Mean, often referred to as the “average,” is a central measure of a dataset. It is calculated by summing up all values in a dataset and then dividing by the total number of data points. The formula for calculating the mean of a dataset with n data points is:

``Mean (μ) = Σ(x) / n``

Here, Σ(x) represents the sum of all data points.

Example: Suppose you have a list of test scores: `[85, 92, 78, 95, 88]`. To find the mean score, sum all the values and divide by the number of scores:

``Mean = (85 + 92 + 78 + 95 + 88) / 5 = 87.6``

So, the mean test score is 87.6.

## 2. Median

The median is the middle value of a dataset when it’s arranged in ascending or descending order. If there’s an even number of data points, the median is the average of the two middle values. In a dataset with n data points:

• If n is odd, the median is the value at position `(n+1)/2`.
• If n is even, the median is the average of the values at positions `n/2` and `(n/2) + 1`.

Example: Consider the dataset: `[12, 45, 67, 23, 98, 54]`. When arranged in ascending order, it becomes: `[12, 23, 45, 54, 67, 98]`. Since there are 6 data points (even), the median is the average of the values at positions 3 and 4:

``Median = (45 + 54) / 2 = 49.5``

So, the median of the dataset is 49.5.

## 3. Mode

The mode is the value that appears most frequently in a dataset. A dataset can have one mode (unimodal), more than one mode (multimodal), or no mode at all if all values occur with the same frequency.

Example: In the dataset `[5, 7, 8, 2, 7, 5, 8, 3, 7]`, the number `7` appears most frequently (three times). Therefore, the mode of this dataset is `7`.

## Python Examples

Let’s put these concepts into action with Python code examples:

### Mean Calculation in Python

``````# Python code to calculate the mean
data = [85, 92, 78, 95, 88]
mean = sum(data) / len(data)
print("Mean:", mean)``````

### Median Calculation in Python

``````# Python code to calculate the median
data = [12, 45, 67, 23, 98, 54]
data.sort()
n = len(data)
if n % 2 == 0:
median = (data[n//2 - 1] + data[n//2]) / 2
else:
median = data[n//2]
print("Median:", median)``````

### Mode Calculation in Python

``````# Python code to calculate the mode
from statistics import mode
data = [5, 7, 8, 2, 7, 5, 8, 3, 7]
mode_value = mode(data)
print("Mode:", mode_value)``````

By mastering these statistical measures, you’ll be better equipped to analyze and interpret data, a crucial skill in the world of Python programming and data science. Happy learning!