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Fall 2008
6.13 If X is binomial with parameters n = 150, p=.6,
compute the exact value of P(X 80) and compare
with its normal approximation both (a) making use of
and (b) not making use of the continuity correction.
_
P(X 80) = 0.057459562
using the Excel 2007 BINO
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Section 5.5: Normal Random Variables_
The normal or bellshaped distribution is the
cornerstone of most methods of estimation and
hypothesis testing developed in the rest of this
course.
The probabilitydensity function (pdf) of the
continuous ra
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
CHAPTER 6: RISK AVERSION AND
CAPITAL ALLOCATION TO RISKY ASSETS
PROBLEM SETS
1.
(e)
2.
(b) A higher borrowing rate is a consequence of the risk of the borrowers default.
In perfect markets with no additional cost of default, this increment would equal the
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STA2001
Statistical Analysis
for Business
Department of Mathematics and Statistics
Hang Seng Management College
1
Unit 3
Regression Analysis and
Correlation
3.1 Simple Linear Regression
2
Introduction
Regression Analysis is used to predict the
value of on
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STA2001
Statistical Analysis
for Business
Department of Mathematics and Statistics
Hang Seng Management College
Unit 1
Estimation
1.1 Introduction
2
What is Statistics?
Statistics is the branch of mathematics that transforms
numbers into useful informatio
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
Hang Seng Management
College
STA102
Statistical Analysis for
Business
Lecturer: Mr Alex Yan Hon Wong)
Office: Rm M252
Email: alexwong@hsmc.edu.hk
STA102
Chapter 3
Regression Analysis &
Correlation
1. Introduction
Regression Analysis is used to
explore the
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
Hang Seng Management
College
STA102
Statistical Analysis for
Business
Lecturer: Mr Alex Yan Hon Wong)
Office: Rm M252
Email: alexwong@hsmc.edu.hk
STA102
Chapter 4
Time Series Analysis
& Forecasting
1. Introduction
An investor is considering buying
HSBC st
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
Hang Seng Management
College
STA102
Statistical Analysis for
Business
Lecturer: Mr Alex Yan Hon Wong
Office : Rm M252
Email
: alexwong@hsmc.edu.hk
Lectures, Tutorials, and Rules:
1) 1 lecture & 1 tutorial (with 90 mins each) per
week but note that each la
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STA2001
Statistical Analysis
for Business
Department of Mathematics and Statistics
Hang Seng Management College
1
Unit 2
Hypothesis Testing
2.1 Null hypothesis vs.
alternative hypothesis
2
2.1.1 Concepts of Hypothesis
Testing
3
2.1.1 Concepts of Hypothesi
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
Hang Seng Management
College
STA102
Statistical Analysis for
Business
Lecturer: Mr Alex Yan Hon Wong
Office: Rm M252
Email: alexwong@hsmc.edu.hk
STA102
Chapter 2
Hypothesis Testing
1. Introduction
Example:
Weight of packets of rice in supermarket.
Suppose
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Sections 6.16.3: Distributions of Sampling Statistics Sample Mean & Total_
By suitably sampling from a population and
analyzing the sampled items, one hopes to be able to
draw some conclusions about the population.
sampling distribution probabil
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Section 8.1: Introduction_
hypothesis testing a procedure, based on sample
evidence and probability, used to test claims
regarding a characteristic of one or more populations.
hypothesis a statement about a population, usually
of the form that a
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Chapter 1: Introduction to Statistics
What is Statistics?
Statistics is the art (and science) of
designing studies
and
analyzing the data that those studies
produce.
Its ultimate goal is translating data into
knowledge and understanding of the wo
The Hong Kong University of Science and Technology
STAT 155
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Fall 2008
STAT 155
Section 2.6: Paired Data Sets and the Sample Correlation Coefficient_
Categorical vs. Categorical
use a contingency table
Categorical vs. Quantitative
compare the categories using
o summaries of center and spread
for the quantitative variable
o
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STAT 155
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Fall 2008
STAT 155
Section 2.2 (cont.): Descriptive Statistics_using Graphs_
Line Graph (Line Histogram)
A line graph plots the distinct data values on the
horizontal axis and indicates their frequencies by the
heights of vertical lines.
Dot Plot
A dot plot shows a
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STAT 155
STAT 155

Fall 2008
STAT 155
Section 3.6  3.8: Conditional Probability, Bayes Formula, and Independent Events _
Multiplication Rule for Independent Events
P(A and B) = P(A) x P(B)
Two events A and B are independent if knowing that one occurs
does not change the probability
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Section 3.1: Elements of Probability Introduction_
Probability allows us to make the inferential jump
from a sample to a population.
In this chapter, probability is defined and some rules
for working with probabilities are introduced.
Chance b
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STAT 155
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Fall 2008
STAT 155
Sections 4.1 4.2: Random Variables_& Types of Random Variables_
Continuous Probability Distributions
f(x) is often referred to as the density curve
P(a X b) the area under the density curve between a and b
P ( a X b) P ( a X b) P ( a X b) P ( a X
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STAT 155
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Fall 2008
STAT 155
Section 7.3: Interval Estimates_
Inferential Statistics: 1) Estimation
and
2) Hypothesis Testing
Problems of estimation are covered in this chapter,
and problems of hypothesis testing are discussed in
chapter 8.
Estimation of parameter(s)
1. obta
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
STAT 155
Sections 4.1 4.2: Random Variables_& Types of Random Variables_
random variable a numerical measurement of the
outcome of a random phenomenon, so its value is
determined by chance. Random variables are denoted
using letters such as X.
90
Discret
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STAT 155
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Fall 2008
STAT 155
Sections 4.5 & 4.7: Properties of the Expected Value & the Variance _
Properties of the Expected Value
If a and b are constants,
then E(aX + b) = aE(x) + b.
 This implies the expected value of a
constant is just its value.
 This also implies t
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STAT 155
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Fall 2008
STAT 155
Section 2.3: Descriptive Statistics_using Numbers_
Measures of Center
mean
median
mode
_
arithmetic mean sum of all the observations divided by
the number of observations.
sample mean:
x
=
_
The arithmetic mean is the most widely used measure
The Hong Kong University of Science and Technology
STAT 155
STAT 155

Fall 2008
THE CHINESE UNIVERSITY OF HONG KONG
Department of Statistics
STAT3002: Experimental Design
Exercises for Week 10
1. (Chapter 6, Exercise 7 in Dean and Voss) Weld Strength Experiment
The data shown in Table 1 are a subset of the data given by Anderson and