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AEA505Agricultural Sciences2 Unitsintermediate

Econometrics

This course introduces students to the fundamental concepts and techniques of econometrics. It covers the definition and scope of econometrics, methodology, types, and importance. Students will learn regression analysis, parameter estimation using ordinary least square method, correlation analysis, problems in regression analysis, and analysis of variance. The course aims to provide a solid foundation for understanding and applying econometric methods in agricultural economics and related fields.

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260h
Study Time
13
Weeks
20h
Per Week
intermediate
Math Level
Course Keywords
EconometricsRegression AnalysisCorrelationANOVAOLS

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
📊
Math Level
Moderate Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Econometrics

2

Regression Analysis

3

Correlation Analysis

4

Analysis of Variance (ANOVA)

5

Hypothesis Testing

6

Ordinary Least Squares (OLS)

Total Topics6 topics

Ready to Start

No specific requirements needed

This course is designed to be accessible to all students. You can start immediately without any prior knowledge or specific preparation.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assignments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

Econometrician

Apply your skills in this growing field

Data Analyst

Apply your skills in this growing field

Statistician

Apply your skills in this growing field

Agricultural Economist

Apply your skills in this growing field

Policy Analyst

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

AgricultureEconomicsFinanceGovernmentResearch

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Introduction to Econometrics

4h

Unit 1: Definition and Scope of Econometrics

4 study hours
  • •Read the definition and scope of econometrics.
  • •Differentiate between economic theory, mathematical economics, and econometrics.
  • •Attempt the tutor-marked assignment.
Week
2

Module 1: Introduction to Econometrics

4h

Unit 2: Methodology of Econometrics

4 study hours
  • •Explain the traditional stages of econometric research.
  • •Understand the differences between mathematical and econometric models.
  • •Work through examples of econometric methodology.
Week
3

Module 1: Introduction to Econometrics

4h

Unit 3: Types and importance of Econometrics

4 study hours
  • •Identify and explain the types of econometrics analysis.
  • •Discuss the importance of econometrics in analysis, policy-making, and forecasting.
  • •Complete the tutor-marked assignment.
Week
4

Module 2: Regression Analysis

4h

Unit 1: Definition and types of Variables

4 study hours
  • •Understand the meaning of variables in econometrics.
  • •Differentiate between continuous, categorical, dummy, and polychotomous variables.
  • •Relate variables to regression models.
Week
5

Module 2: Regression Analysis

4h

Unit 2: Meaning and types of Regression Analysis

4 study hours
  • •Explain the meaning of regression analysis.
  • •Understand the types of regression models.
  • •Differentiate between regression and causation.
Week
6

Module 2: Regression Analysis

4h

Unit 3: Non-linear Regression Analysis

4 study hours
  • •Explain the meaning of non-linear regression analysis.
  • •Distinguish between linearity in variables and parameters.
  • •Identify intrinsically linear and nonlinear regression models.
Week
7

Module 2: Regression Analysis

4h

Unit 4: Data for Regression Analysis

4 study hours
  • •Identify data sources for estimating regression parameters.
  • •Explain the various types of data required for model estimation.
  • •Differentiate between cross-section, time series, pooled cross-section, and panel data.
Week
8

Module 3: Parameter Estimates Using Ordinary Least Square (OLS) Method

4h

Unit 1: Techniques for Estimating Parameters of Regression Models and Assumptions on Ordinary Least Square (OLS) Estimates

4 study hours
  • •Identify techniques for estimating parameters of regression models.
  • •Understand the assumptions of ordinary least squares (OLS).
  • •Discuss stochastic assumptions and assumptions concerning independent variables.
Week
9

Module 3: Parameter Estimates Using Ordinary Least Square (OLS) Method

4h

Unit 2: Causes of Deviation of Observation from the fitted line

4 study hours
  • •Explain the causes of deviation of observation from the fitted regression line.
  • •Understand the problems that can arise in linear regression models.
  • •Review the table summarizing problems in linear regression models.
Week
10

Module 3: Parameter Estimates Using Ordinary Least Square (OLS) Method

4h

Unit 3: The Ordinary Least Squares Method (OLS)

4 study hours
  • •Apply OLS method to estimate regression parameters.
  • •Use both actual observation and deviation methods.
  • •Interpret parameter estimates.
Week
11

Module 3: Parameter Estimates Using Ordinary Least Square (OLS) Method

4h

Unit 4: Parameter Testing (Hypothesis formulation and Testing)

4 study hours
  • •Define hypothesis and differentiate between null and alternative hypotheses.
  • •Formulate hypotheses and apply appropriate statistical tools for testing.
  • •Use standard error, t-test, and F-test for hypothesis testing.
Week
12

Module 4: Correlation Analysis

8h

Unit 1: The meaning of Correlation

4 study hours
  • •Describe correlation and understand its scope.
  • •Differentiate between simple and multiple correlation.
  • •Compute correlation coefficient using Pearson's Product Moment Correlation Coefficient.

Unit 2: Types/forms of Correlation

4 study hours
  • •Describe the types and forms of correlation.
  • •Understand linear, non-linear, and zero correlation.
  • •Use diagrams to explain different types of correlation.
Week
13

Module 4: Correlation Analysis

4h

Unit 5: Limitations of Linear Correlation and Correlation versus Regression

4 study hours
  • •Understand the limitations of linear correlation.
  • •Compare correlation and regression analyses.
  • •Review the differences between correlation and regression models.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all definitions and formulas from each unit.

2

Practice solving regression problems using different datasets.

3

Focus on understanding the assumptions of OLS and their implications.

4

Create a summary sheet of key concepts and formulas for quick reference.

5

Work through all tutor-marked assignments and understand the solutions.

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