Quantitative Techniques for Business 203
Tutorial 8 Solutions
Felix Chan
March 2014
Question 1. Let X N (1, 4), find P (X > 0), P (1 < X < 1), P (1 < X < 1.5) and
P (X < 3).
Solution: Let z = (X + 1)/2, i.e. z is the standardized version of X.
P (X > 0) =

Quantitative Techniques for Business 203
Tutorial 2 Solutions
Felix Chan
March 2014
Question 1. Let X1 be a random variable representing the outcome of rolling a six-sided
die (assuming fair). Write down all the possible outcomes and their probabilities.

Quantitative Techniques for Business 203
Tutorial 7 Solutions
Felix Chan
March 2014
Question 1. Let X be a discrete random variable with 5 possible outcomes, namely
cfw_3, 1, 0, 1, 2, with probabilities cfw_0.2, 0.1, 0.3, 0.3, 0.1.
a. Calcualte E(X), E(X

Quantitative Techniques for Business
Tutorial 9
Felix Chan
April 2014
Question 1. Download the file tutorial04 q2.xlsx from Blackboard. The file contains the
population data for the variable X. Let Xi be a random variable representing a random
draw from X

Quantitative Techniques in Business
Tutorial 10
Felix Chan
September 2014
Question 1. Download the file tut10.xlsx from Blackboard. In the file there are
two sets of data, each with 200 observations. The first column contains the returns of
firms that off

Quantitative Techniques for Business 203
Tutorial 3 Solutions
Felix Chan
March 2014
Question 2. Let X N (1, 2), find P (X > 0), P (1 < X < 1), P (1 < X < 1.5) and
P (X < 3).
Solution: Let z = (X + 1)/2, i.e. z is the standardized version of X.
P (X > 0) =

Quantitative Techniques for Business 203
Project
School of Economics and Finance
Curtin University
Felix Chan
July 2014
1
Introduction
The aim of this project is to evaluate different portfolio compositions of financial
assets based on time series data. I