Pearson Correlation (r) – Elldy Academy

What is data analytics?

Data cleaning? Missing Values Duplicate Data Case Sensitivity Data Types Outliers

Quick Stats Basic Stats What Is an Outlier? How to Practice Basic Stats & Outliers

1. Variance 2. Standard Deviation (SD) 3. Coefficient of Variation (CV) 4 Practice Variance, Standard Deviation (SD), Coefficient of Variation (CV)

1. Skewness 2. Kurtosis

Correlation Why We Use Correlation? Pearson Correlation (r) Spearman Correlation (ρ or rₛ)

Trend Analysis 1. Time forecasting 2. Trend Break Detection 3 Moving Average

Grouping 1. Group By Sum 2. Group By Mean (Average) 3. Group By Count 4. Group By Minimum 5. Group By Maximum 6. Group By Median

AI Insights 1. Anomaly Detection 2 .Forecast Suggestion (Predictive Forecasting) 3 Correlation Warning 4 Trend Direction Prediction 5 Seasonality Detection 6 Top Driver / Influencer Analysis 7 Productivity Improvement Prediction 8 Business Risk Warnings

CERTIFICATION

chapter 6 : Correlation

Pearson Correlation (r)

Lesson Image

Measures linear relationships — relationships that can be shown with a straight line.

Works best when both variables are continuous, normally distributed, and have no extreme outliers.

Result is a value between –1 to +1:

+1 → strong positive linear relationship
–1 → strong negative linear relationship
0 → no linear relationship
Example: Height and weight often show a positive Pearson correlation.

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