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8.1 Introduction

Correlation and regression are essential statistical techniques for analyzing relationships between variables, crucial for informed decision-making and predicting outcomes. Correlation measures the strength and direction of linear relationships, while regression models the dependency between dependent and independent variables. These methods uncover hidden patterns and enhance predictive capabilities in data analysis.

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8 views1 page

8.1 Introduction

Correlation and regression are essential statistical techniques for analyzing relationships between variables, crucial for informed decision-making and predicting outcomes. Correlation measures the strength and direction of linear relationships, while regression models the dependency between dependent and independent variables. These methods uncover hidden patterns and enhance predictive capabilities in data analysis.

Uploaded by

osama7abx
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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8.

1_Introduction
Introduction

Correlation and regression are two fundamental statistical techniques used to


examine (‫ )يفحص‬and quantify (‫ )تحديد الكمية‬relationships between variables.
In real-world data analysis, understanding how variables interact is crucial for making
informed decisions (‫)قرارات مستنيرة‬, predicting future outcomes, and uncovering
hidden patterns .
Unlike basic statistical measures such as mean, median, and standard deviation, which
primarily describe individual variables, correlation and regression focus on the
interdependencies (‫ )الترابط‬and predictive power (‫ )القوة التنبؤية‬between variables.

Why Do We Need Correlation and Regression ?


Correlation helps us measure the strength and direction of the linear relationship
between two quantitative variables.
Regression, on the other hand, goes beyond measuring relationships—it models the
dependency between a dependent variable and one or more independent
variables .
This makes regression an essential tool for prediction .

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