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To stimulate student‘s knowledge on normal linear regression model
To make the students to understand some of the practical aspects of econometrics
test.
To expose the students to rudimentary analysis of simple
and multiple regression
analysis.
Course Objectives
To achieve the aims of this course, there are overall objectives which the course is out to
achieve though, there are set out objectives for each unit. The unit objectives are included
at the beginning of a unit; you should read them before you start working through the
unit. You may want to refer to them during your study of
the unit to check on your
progress. You should always look at the unit objectives after completing a unit. This is to
assist the students in accomplishing the tasks entailed in this course. In this way, you can
be sure you have done what was required of you by the unit. The objectives serves as
study guides, such that student could know if he is able to grab the knowledge of each
unit through the sets of objectives in each one. At the end of the course period, the
students are expected to be able to:
to understand the basic fundamentals
of Econometrics
distinguish between Econometrics and Statistics.
know how the econometrician proceed in the analysis of an economic problem.
know how the econometrician make use of both mathematical and statistical
analysis in solving economic problems.
understand the role of computer in econometrics analysis
identify/explain the types of econometrics analysis.
understand the basic Econometrics models
differentiate between Econometrics theory and methods
know the meaning of Econometrics and why Econometrics
is important within
Economics.
know how to use Econometrics for Assessing Economic Model
understand what is Financial Econometrics.
examine the linear regression model
understand the classical linear regression model
be able to differentiate the dependant and independent variables.
prove some of the parameters of ordinary least estimate.
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know the alternative expression for
̂
understand the assumptions of classical linear regression model.
know the properties that our estimators should have
know the proofing of the OLS estimators as the best
linear unbiased estimators
(BLUE).
examine the Goodness fit
understand and work through the calculation of coefficient of multiple
determination
identify and know how to calculate the probability normality assumption for U
i
understand the normality assumption for U
i
understand why we have to conduct the normality assumption.
identify the properties of OLS estimators under
the normality assumption
understand what is probability distribution
understand the meaning of Maximum Likelihood Estimation of two variable
regression Model.
understand the meaning of Hypothesis
know how to calculate hypothesis using confidence
interval
analyse and interpret hypothesis result.
understand the meaning of accepting and rejecting an hypothesis
identify a null and alternative hypothesis.
understand the meaning of Level of significance
understand the Choice between confidence-interval and test-of-significance
Approaches to
hypothesis testing
understand the meaning of regression analysis and variance
know how to calculate the regression analysis and analysis of variance
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