Lecture 10
Time Series Analysis
1
Introduction
2
What is a time series?
A series of
observations on a
variable of interest over
a sequence of equal
time periods
Example: quarterly
Australian retail
turnover during the past
decades. (Some rows
are hidden!)

Lecture 5
Estimation and Hypothesis test
- Probability distributions (Chp.5)
1
Probability Distributions
A probability distribution specifies the
probabilities of the possible outcomes of a
random variable.
Random variable: a quantity whose future
outcome

Lecture 6
Sampling and Estimation
&
Hypothesis test
1
Sampling and Estimation
In empirical studies, we are often
interested in obtaining information about
the value of some parameter of a
population.
To obtain this information we usually take
a smaller su

Lecture 7
Correlation and Regression
1
Section 1: Correlation
A scatter plot is a graph that shows the relationship
between the observations for two data series in two
dimensions.
Scatter Plot of Money Supply Growth and Inflation rates
(Data available in

Lecture 3
Statistical concepts
1
Statistical Concepts
Statistics provides powerful tools for analyzing data
such as stock prices, asset returns.
Descriptive statistics allow us to determine the central
tendency, dispersion, and skewness of a set of data.

Lecture 8
Simple Linear Regression Analysis
(Cont.)
1
LINEARITY AND NONLINEARITY
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X
Here is the scatter diagram for two variables X and Y.
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LINEARITY AND NONLINEARITY
Y
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Lecture 4
Probability concepts
1
Probability Concepts
Probability allows us to make decisions in an
environment of risk (uncertainty).
The probability of event A occurring is denoted by
P(A).
P(A)=(Number of times A occurs)/(Number of
possible outcome)
W

Lecture 11
Portfolio Theory & Management
1
Mean-Variance Analysis
Meanvariance portfolio theory is based
on the idea that the value of investment
opportunities can be meaningfully
measured in terms of mean return and
variance of return.
2
Assumptions of t