C+ Programming:
From Problem Analysis
to P
t Program Design, Third Edition
D i
C apte 3: put/Output
Chapter 3 Input/Output
Objectives
In this chapter you will:
o
ill
Learn what a stream is and examine input
and output streams
Explore how to read data fr

Multiplication Rule
If in an experiment the events A and B can both occur, then
P A B P B A P A P A B P B
Total Probability Rule (two events)
For any events A and B,
P B P B A P B A P B A P A P B A P A
Example 1
The probability that the first stage of a

Definition
P A B
P B A P A
P B
for P B 0
Bayes Theorem
If E1, E2, , Ek are k mutually exclusive events and B is any event.
Then,
P E1 B
for P B 0.
P B E1 P E1
P B E1 P E1 P B E2 P E2
P B Ek P Ek
Example 1
Because of new medical procedure has been sh

Independence (two events)
Two events are independent if any one of the following is true:
(a) P A B P A
(b) P B A P B
(c) P A B P A P B
Independence (multiple events)
The events E1, E2, , En are independent if and only if for any
subset of these events

Probability
Used to quantify likelihood or chance
Used to represent risk or uncertainty in engineering applications
Can be interpreted as our degree of belief or relative frequency
Equally Likely Outcomes
Whenever a sample space consists of N possible out

2.1.1
Random Experiment
Definition
2.1.2
An experiment that can result in different outcomes,
even though it is repeated in the same manner every
time, is called a random experiment.
Sample Spaces
Definition
The set of all possible outcomes of a random
ex

TOPIC 6: MAXIMUM
LIKELIHOOD METHODS
6.1MLE
6.2 Rao-Cramer Lower Bound & Efficiency
6.3 Maximum Likelihood tests
1. Maximum Likelihood Estimation (MLE)
The basis inferential procedures:
1. Likelihood function
2. Calculation of MLE
3. Properties of MLE
Like

STQS2133 PENTAABIRAN
STATISTIK
KULIAH 1: PENGENALAN
BEBERAPA ASAS PENTAABIRAN
STATISTIK
4.1 Pensampelan dan statistik
Pemboleh ubah rawak
Dalam masalah biasa statistik, kita biasanya mempunyai
pemboleh ubah rawak yang diminati, X; tetapi kita tidak
ketah

Course: Distributed Computing
Systems
Lecturer: Dr. Izzatdin Bin Abdul Aziz
Project Theme: Switch Based LANs
and Internet
Project Proposal Report:
Static IP in LAN & Port Forwarding
Group Members:
KUNASHALINI PONGKUNRAN 16453
RAGHULAN 18520
INTRODUCTION
I

TCB 3343 Artificial Intelligence
Introduction
1
Learning Outcomes
At the end of the lecture, you will be able to:
understand intelligence and artificial
intelligence
know the foundations and history of AI
explore the AI Research Areas
2
What is intelli

Searching
1
LEARNING OUTCOMES
To understand graph theory and
searching
To do blind search and heuristic search
techniques
2
Graph Theory
Graph theory was inspired by the Seven Bridges of
Knigsberg.
The city of Knigsberg, Russia is set on the Pregel Ri

Natural Language Processing
1
Learning Outcomes
To understand the structures of Natural Language
To do Grammar and Parsing
2
What is NLP?
Natural Language refers to the language spoken
by people, e.g. English, Japanese, Arabic, French,
Malay, etc.
to repr

To introduce conditional probability, consider an example
involving manufactured parts.
Let D denote the event that a part is defective and let F denote
the event that a part has a surface flaw.
Then, we denote the probability of D given, or assuming, th

Probability of a Union
If A and B are two events, then
P A B P A P B P A B .
Mutually Exclusive Events
If A and B are mutually exclusive, then
P A B P A P B
Three Events
For three events A, B, and C,
P A B P A P B P C
P A B P A C P B C P A B C .
Mutual

Introduction to Six Sigma
Use of statistics & other analytical tools has grown steadily for
over 80 years
Statistical quality control (origins in 1920, explosive growth
during WW II, 1950s)
Operations research (1940s)
TQM (Total Quality Management) mov

PANDUAN PEMBELAJARAN KURIKULUM PENDIDIKAN PEMANDU
PANDUAN PEMBELAJARAN KURIKULUM PENDIDIKAN PEMANDU
KANDUNGAN
Semua hakcipta terpelihara. Sebarang bahagian di dalam buku ini
tidak boleh di terbitkan semula, disimpan dalam cara yang boleh
dipergunakan lagi

(Question 1)
State the level of measurement as Nominal, Ordinal, Interval or Ratio for
each variable as shown below
Column Name
EDUCATION
LIVES_IN_SOUTH
INCOME STATUS
EXPERIENCE
WAGE
AGE
RACE
Explanation
Values
Measure
2 to 18
Number of years
of
Indicator

Question 5
A restaurant claims that the standard deviation in the length of serving times is less than 2.9 minutes.
A random sample of 23 serving times has a standard deviation of 2.1 minutes. At =0.10,is there are
enough evidence to support the restauran

[KKKQ2024 ENGINEERING STATISTICS] SEM2 2014/2015
Exercises 1
(Chapter 2)
1.
The resumes of 2 male applicants for a college teaching position in chemistry are placed in the
same file as the resumes of 2 female applicants. Two positions become available and

[KKKQ2024 ENGINEERING STATISTICS] SEM2 2014/2015
Exercises 2
(Chapter 3)
1.
A shipment of 7 television sets contains 2 defective sets. A hotel makes a random purchase
of 3 of the sets. If x is the number of defective sets purchased by the hotel, find
2.
a

[KKKQ2024 ENGINEERING STATISTICS] SEM2 2014/2015
Exercises 3
(Chapter 4)
1.
2.
3.
4.
The breakdown of an industrial machine follows a Poisson process with a mean of 2.3
per year.
(a)
What is the expected time between machine breakdowns?
(b)
What is the pr

Problem Perfect Competition
1. Is the following statement true or false? Explain why. In the short run, the supply curve
will be upward sloping.
2. Is the following statement true or false? Explain why. In long run equilibrium, if firms
in a perfectly com

Quality
Quality:A subjectve term for which each person or
sector has its own definiton.
In technical usage, quality can have two meanings:
1. the characteristcs of a product or service that bear on its
ability to satsfy stated or implied needs;
2. a p

Desain dan Analisis Algoritma
Pertemuan 5
Asymptotic Notations
Latihan
Tentukan kelas OOG algoritma Tower of
Hanoi
Latihan
algorithm secret(n)
/input bilangan bulat positif n
If n = 1 return 1
else return secret ([n / 2]) + 1
Apa yang dilakukan algoritma

SEVEN QUALITY TOOLS
Cause and Effect Diagrams
Check sheets
Control Charts
Histograms
Pareto Charts
Scatter Diagrams
Flow Charts
FISHBONE (ISHIKAWA) DIAGRAM
The fishbone diagram identifies many
possible causes for an effect or problem.
It can be used to st