Process Analysis II
Capacity, Bottleneck, Utilization, Cycle time
1
Imagine you are managing a large bakery with products
ranging from breads to pies. Your mission is to improve
the profitability of the operation. How will you start?
Production is not the

Process Analysis I
Flow Time, Flow Rate, Inventory
1
The Customer in a Supermarket
The amount of time spent in a supermarket by
customers is of interest to the management.
How would you go about finding the average time
that customers spend in the store?

Service System Design Issues
Ronald S. Lau, Ph.D.
HKUST ISOM
Direct and Design
Plan and Control
Develop
Introduction
Demand Forecasting
Quality Management
Strategic Design
Capacity and Revenue
Management
Best Practices and
Improvement
Service Concepts
and

1. A game of chance consists of rolling three ordinary six-sided dice.
The player bets $1 per
game, and wins $1 for each occurrence of the number 6 on any of the dice (retaining the
original bet in that case). Thus the net amount won would be $1, $2, $3 o

Practice Final
1. The slope ( ) represents
(a) predicted value of Y when X = 0.
(b) the estimated average change in Y per unit change in X.
(c) the predicted value of Y.
(d) variation around the line of regression.
2. The residual scatter plot on the righ

ISMT111 (L2) Business Statistics
Quiz 1
March 10, 2005
Directions
1.
There are 6 pages in this examination paper (including this). Check to make
sure you have a complete set and notify the invigilator immediately if part of it
is missing.
2.
Key formulas

Multiple Choice 2009 Chapter 1
1.Economics is best defined as
a. how people make money and profits in the stock market.
b. making choices from an unlimited supply of goods and services.
c. making choices with unlimited wants but facing a scarcity of resou

Lecture 4: Basic Probability (Part I)
We encounter uncertainties such as the following:
What is the likelihood that the project will be nished on
time?
What are the odds that a new investment will be protable?
Probability is the likelihood or chance that

The Hong Kong University of Science and Technology
ISMT-111 Business Statistics, Spring 2006 (L1)
Homework 7 Solutions
Q1/
(i.e. Question 9 of Problem sheet 6)
a/
Sxx = Sx 2 x (n-1) = (2.5)2 x 101 = 631.25
Syy = Sy 2 x (n-1) = (2.0)2 x 101 = 404
b/
1 =
Sx

1. Question 9 of problem sheet 6
2. Question 10 of problem sheet 6
3. The Central Company manufactures a certain specialty item once a month in a batch production run. The number of items produced in each run varies from month to month as
demand
uctuates

1. Let X = # of times number 6 shows up out of 3 rollings of dice, Y =the amount won from
one bet. Note that X B (3; 1=6)
(a) P (Y = $1) = P (X = 1) = 3
P (Y = $2) = P (X = 2) = 3
P (Y = $3) = P (X = 3) =
(b) E (Y ) =
53
C 3 C1
8
C4
+
(1=6)2
(5=6) = 0:069

1. The results of the midterm examination in one section of ISMT 111 are summarized as follows:
Number of students
100
Mean
80
Sample standard deviation
12
Median
77
Minimum
43
Maximum
98
First quartile
68
Third quartile
82
One student appealed and the in

Lecture 13: Large sample hypothesis testing
Hypothesis test for population mean
1. Null Hypothesis:
H0 :
:
=0
2. Alternative Hypothesis:
Two tailed
Ha: 6= 0 Ha:
3. Test statistic
x
p0
=n
is unknown, substitute with s:
z=
if
one tailed
> 0 Ha :
1
<0
4. Rej

Lecture 5: Basic Probability (Part II)
Conditional probability:
Let B be an event such that P (B ) > 0: Then, the conditional
probability that event A occurs given that event B is known
to have occurred is given by the ratio:
P (AB )
P (AjB ) =
P (B )
1
E

Lecture 6: Discrete probability distributions
Some of the outcomes we discussed, like the outcome of a coin
toss, are qualitative in nature, and it is often more convenient
to work with outcomes that are quantitative.
Denition:
A random variable is a nume

Lecture 7: Important discrete distributions
Bernoulli trials are the ones with the following characteristics:
The trials are independent. i.e., the outcome of one trial does
not aect the outcome of the other.
Two mutually exclusive outcomes in each trial:

Lecture 9: Sampling distributions
Understanding Sampling distribution: Suppose there are
four salesperson (A, B, C, D) making up a population (N = 4).
Salesperson Units sold
A
2
B
4
C
6
D
8
A random sample of size n = 2 subjects from the population
1
with

Lecture 10: Condence interval Estimation I (Large
sample)
A point estimate consists of a single number based on sample
data that is used to estimate the true value of a population
parameter. It is the best guess of the value of a parameter
Ex: sample mean

Lecture 11: Condence interval estimation II
(small sample)
Estimating population mean
Ex: Suppose management has agreed to train 15 employees using the computer-assisted program. The data on training
days required for each employee in the sample are liste

Lecture 12: Introduction to hypothesis testing
Example 1: If you are the manager of a manufacturing plant
which produces coee. The label on a large can states that the
can contains three pounds. You want to make sure that the
coee cans produced meet the s

ISMT111 Business Statistics
Final Examination
For section L2 only
13th December 2004
Directions
1) Answer ALL SIX questions. Marks are shown in square brackets.
2) There are 5 pages in this examination paper. Check to make sure you
have a complete set and

ISMT111 Business Statistics
Final Examination
For section L2 only
13th December 2004
Directions
1) Answer ALL SIX questions. Marks are shown in square brackets.
2) There are 5 pages in this examination paper. Check to make sure you
have a complete set and

The Hong Kong University of Science and Technology
ISMT-111 Business Statistics, Fall 2005
Problem sheet 6
Solutions (Supplementary)
1. a.
Y i = b0 + b1Xi
b1 =
SSXY
SSX
where SSXY = XY -
X Y
n
107 x107
= 1222 10
= 77.1
SSX = x2 -
( x)2
n
107 ^ 2
= 1189 1

1. (5 7)Let
1
(a) H0 :
be salary for Bachelor degree holder and
s
2
1
= 1000; Ha :
(b) Test statistic z =
2
1
(6200 5000) 1000
q
2
3002
+ 220
50
50
2
be salary for Master degree holder
s
> 1000
= 3:80
(c) Since z > z0:05 = 1:645, reject H0 and claim that

ISMT111 Business Statistics
Quiz 2
April 25, 2006
Directions
1.
There are 4 pages in this examination paper (including this). Check to make
sure you have a complete set and notify the invigilator immediately if part of it
is missing.
2.
Key formulas and s

ISMT111 Business Statistics
Quiz 2
April 21, 2005
Directions
1.
There are 5 pages in this examination paper (including this). Check to make
sure you have a complete set and notify the invigilator immediately if part of it
is missing.
2.
Key formulas and s

ISMT111 (L1) Business Statistics
Quiz 1
March 7, 2006
Directions
1.
There are 7 pages in this examination paper (including this). Check to make
sure you have a complete set and notify the invigilator immediately if part of it
is missing.
2.
Key formulas a

Sampling distribution:
1. If X1 ; X2 ; :; Xn is a sample from a population with mean
2,
and variance
E X = ; s:e: X = p
2. If X1 ; X2 ; :; Xn is a sample from a normal population with mean
N( ;
n
) or equivalently
X
p
=n
2,
3. If the population in (1) is

ISMT 111 BUSINESS STATISTICS TUTORIAL 8
created by Andrew Yam
Simple Linear Regression Model
Aim: Use X (Independent Variable, or Predictor Variable) to
predict Y (Dependent Variable, or Response Variable) after
drawing n pairs of observations, (x1 , y 1