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Correlation & Regression Analysis

In everyday life we can find plenty of examples of relationships between variables, whether physical, social, economic, political, or otherwise. For example, there exists a clear and direct relationship between the height of a person’s body and his weight. Also, there is a relationship between income and consumption, both for an individual and for a country.

Two simple and meaningful ways to measure the relationships among variables are the statistical concepts of correlation and regression analysis. This course describes these techniques, and provides some examples of how they are applied in the financial world

OBJECTIVES

On completion of this course, you will be able to:

• Describe the concept of correlation and compute the correlation coefficient between two variables

• Use regression analysis to model the relationship between variables

COURSE OUTLINE

Topic 1: Correlation

• Definition of Correlation

• Some Fundamental Concepts

• Pearson Correlation Coefficient

• Types of Correlation

• Interpretation of the Size of the Correlation Coefficient

• Computing Correlation Manually

• Computing Correlation – Example

• Correlation Coefficient of a sample

• Correlation Coefficient of a sample – Example

• Correlation & Causality

Topic 2: Regression Analysis

• Definition of Regression Analysis

• Purpose of Regression Analysis

• Regression Analysis

• Two- Variable Linear Regression

• Ordinary Least Squares (OLS) Regression Analysis

• Derivation of Least Squares Estimators

• Computing the Least Squares Estimators Manually – Example

• Generalization of Ordinary Least Squares

• Assumptions of Progression Analysis

• Properties of the OLS Estimators

PREREQUISITE KNOWLEDGE

A reasonable level of mathematical and statistical knowledge is assumed.

ESTIMATED COMPLETED TIME

75 minutes

Next Course

Calculus

This course introduces the concept of differentiation and its counterpart, integration. Simple economic applications of the two concepts are also described.

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