Correlation

Correlation is a statistical measure that quantifies the degree of association or relationship between two variables. In other words, it helps us understand how two variables tend to move in relation to each other.

Correlation provides a straightforward way to examine the result. The correlation value falls within the range of [-1, 1]. Refer to the table below:

Correlation with Python

To calculate correlation, use the np.corrcoef() function from numpy, which requires two parameters: the data sequences for which correlation is to be computed. Here's an example:


              123456789
            
import pandas as pd
import numpy as np

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a849660e-ddfa-4033-80a6-94a1b7772e23/update/Stores.csv')

# Calculating correlation 
corr = np.corrcoef(df['Store_Area'], df['Items_Available'])[0,1]

print(corr)

Here, we extracted the value at index [0, 1], just like in the case of covariance. In the previous chapter, we obtained the value 74955.85, and interpreting the result of the covariation function can be challenging. However, in this case, we can conclude that the values are strongly related.

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Kursinnhold

Learning Statistics with Python

1. Basic Concepts

Sample vs Population Types of Statistics Types of Data Mean Value Median Value Median Value of the Even Number of Values Mean or Median Mode Value Descriptive Statistics Quiz

2. Mean, Median and Mode with Python

Examine the Dataset Calculating Mean and Median Values with Python Statistics with pandas Calculate the Mean and Median Salary

3. Variance and Standard Deviation

Population Variance Sample Variance Calculate Variance with Python Standard Deviation Standard Deviation with Python Calculating Variance and Standard Deviation

4. Covariance vs Correlation

Covariance Correlation Covariance and Correlation Quiz Calculate Covariance and Correlation

5. Confidence Interval

6. Statistical Testing

What is t-test Hypotheses t-test Mathematically One-Tailed And Two-Tailed Test t-test Assumptions Performing a t-test in Python Conduct a t-test Paired t-test