Question 1
Describe briefly the three hypothesis testing procedures that
are available under maximum likelihood estimation....
Question 1
Describe briefly the three hypothesis testing procedures that
are available under maximum likelihood estimation. Which is likely
to be calculated in practice and why?
What stylized fact of financial data cannot be explained using
linear trend models? ( 10 marks)
Which of these features can be modelled using a GARCH (1,1)
process? ( 10 marks)
(a) Discuss briefly the principles behind maximum
likelihood.
(b) Describe briefly the three hypothesis testing procedures that
are available
under maximum likelihood estimation. Which is likely to be the
easiest
to calculate in practice, and why?
(c) OLS and maximum likelihood are used to estimate the parameters
of a
standard linear regression model. Will they give the same
estimates?
Explain your answer.
What is the the main intuition behind the Maximum Likelihood
estimation method. Is there any connection between Maximum
Likelihood Estimation and the Generalized Methods of Moments?
Carefully motivate your answer.
Describe briefly the aetiology of schizophrenia.
Explain the dopamine hypothesis of schizophrenia.
Outline the options available for the treatment of this disease
and give a detailed description of the use your chosen therapeutic
agent.
n hypothesis testing we set alpha, the significance
level, which limits the likelihood of making a Type 1 error if the
null hypothesis were true. When does a type 2 error occur? Give a
real world example of a decision and explain what the null
hypothesis, alternative hypothesis, type 1 and type 2 errors would
be – which would be worse in this case: making a type 1 error or
making a type 2 error?
Distinguish between data analysis, hypothesis testing modelling
and estimation. Give a simple example of each and discuss the
appropriate contexts in which each should be used.
In
your own words, describe what you have learned about hypothesis
testing and hypothesis testing for the mean. Give one or more
examples of how you could use this information to test a problem.
Be specific on what the problem would be about.
Regression analysis consists of two major tasks: (i) estimation
of population parameters and (ii) hypothesis testing (e.g., t-test,
F-test) or the application of inferential statistics to the
estimated parameters. We learned OLS (ordinary least square)
principle as the major estimation tool (thereby fulfilling the
first task). There is a critically important assumption that we
have to make in order to perform the second task (that is, to
conduct hypothesis testing with respect to estimated parameters).
Identify and discuss it. (10...