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Introductory Econometrics This Course Guide has been taken from the most recent presentation of the course. Aims This course deals with quantitative model building and statistical skills which you will find useful in economics, marketing, risk management, and investment. Course learning outcomes Upon completion of this course, you should be able to: Illustrate some commonly used probability distributions. Apply simple statistical hypotheses.
Course materials This practical topic sets out the materials you'll need for your study of ECON A ; in particular, it introduces you to the course's six study units. Study units The study units are listed and briefly described below. Unit 1 The nature of econometrics and description of major economic data This unit introduces you to the basic concepts related to research methods in economics and business forecasting.
Unit 2 A review of the basics in statistics This unit helps you review the basic statistical skills. Unit 3 The simple linear regression model This unit discusses the basic ideas underlying linear regression in terms of a two-variable model. Unit 4 Multiple regression models This unit focuses on multiple regression, which relates a given dependent variable to several independent variables. Unit 5 Model selection and introduction to simultaneous equations This unit consists of two parts.
Unit 6 Qualitative variables in regression models The variables of the linear regression models in the previous units are numerical or quantitative.
Computer-Aided Introduction to Econometrics - Juan Rodriguez Poo - Google Libros
Assignment There will be two assignments. Presentation Schedule The Presentation Schedule which is available on the OLE gives the dates for completing assignments, attending tutorials, and so on. Assessment Self-tests The self-tests in the study units provide a means for self-assessment. Tutor-marked Assignments There are two assignments and both assignments will be counted in your final grade: Assignment 1 covers the material in Units Assignment 2 covers the material in Units Final examination and grading The final exam will cover all the materials studied in the course.
Tutor and tutorials You will be assigned a tutor for the course. Accessibility Privacy policies Terms and policies Webmaster.
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All Rights Reserved. Introduction What this course helps you do Course materials. Assessment Study schedule How to get the most from this course. What this course helps you do. Each unit takes about two to six weeks to finish, and the whole course takes approximately 14 weeks to complete. Students are expected to spend around 14 hours a week studying this course. You should read them carefully, and come back to them from time to time as you work through the course so that you can give yourself a 'check-up' -- that is, to see if you are meeting these aims and objectives. This course deals with quantitative model building and statistical skills which you will find useful in economics, marketing, risk management, and investment.
It aims to teach you how to use statistical techniques to estimate and test in business and economics.
You will learn how to create a statement of theory or a hypothesis, how to collect data, and how to specify economic and business models. You will also learn how to estimate the parameters of your chosen forecasting model, check for model adequacy, and test the hypotheses derived from the model. Course learning outcomes. Apply regression models to analyse business and economic data, including cases when data are not quantifiable.
Analyse and evaluate the more advanced model-building techniques such as the simultaneous equation system and the logit model. This practical topic sets out the materials you'll need for your study of ECON A ; in particular, it introduces you to the course's six study units. In addition to this Course Guide , the course has the following important components.
Please ensure that you have all of these materials available. This unit introduces you to the basic concepts related to research methods in economics and business forecasting. The essential skills in using a related computer software package, Econometrics Views EViews are also introduced. The unit then describes some major sources of economic data, especially those from Hong Kong.
Some important Hong Kong economic data such as GDP, inflation rate and unemployment rate are also described. This unit helps you review the basic statistical skills. You will learn what a random variable is, and how to differentiate between a discrete random variable and a continuous random variable. You will also learn how to calculate the mean and the variance of a random variable. The unit then briefly discusses some important distributions and theorems in statistics, and the standard procedures for hypothesis testing.
This unit discusses the basic ideas underlying linear regression in terms of a two-variable model.
Computer-aided introduction to econometrics /
You will learn to distinguish between population regression and sample regression, and to estimate a regression model by the method of least squares, which is one of the most popular methods of estimation. You'll also be introduced to the principle of the least squares procedure and learn to apply it to estimate the simple linear regression model. You will then learn to perform hypothesis testing on the linear regression model, and to use the regression model to make simple statistical predictions.
This unit focuses on multiple regression, which relates a given dependent variable to several independent variables. You will learn how to estimate and perform hypothesis testing related to a multiple regression model. In particular, you will learn how to choose the functional forms of regression models. The unit also discusses the problems of multicollinearity, heteroscedasticity and serial correlation in multiple regression.
This unit consists of two parts. The first part focuses on issues related to model selection, including discussion of the types of specification errors and their consequences. You will also learn the procedure for detecting specification errors. The second part of the unit comprises a brief discussion of the simultaneous equations model. You will study the nature of the model and the procedure for estimating the model.
The variables of the linear regression models in the previous units are numerical or quantitative.
europeschool.com.ua/profiles/xocadah/lajor-crucero-a-cerdena.php There are occasions, however, where variables can be qualitative in nature. When the independent variable is qualitative, it is often known as a 'dummy variable'. In this unit, you learn how to estimate a regression model with dummy variables and correctly interpret the regression results. This unit also includes a brief discussion of regression models when the dependent variable is qualitative.
In each unit there are self-test questions and practice exercises. Most of these questions are selected from your textbook and the accompanying instruction manual. Make sure that you attempt all the questions to check that you understand the study units. Some of the data in the study units are formatted in electronic form, with the data presented as Excel files.
You can download the Excel files to work on them. Presentation Schedule.