2
MATLAB Fundamentals
CHAPTER OBJECTIVES
The primary objective of this chapter is to provide an introduction and overview of
how MATLABs calculator mode is used to implement interactive computations.
Specific objectives and topics covered are
Learning how
Lecture week 3
Solution of Nonlinear Algebraic Equations
1
1.1
Solution of Nonlinear Algebraic Equations
Background to the application
In this session you will create simple routines that can be used to find solutions of nonlinear equations.
You will know
Lecture 1
Introduction. Error analyses
1
Preliminaries and outline
Some problems are difficult or even impossible to solve analytically.
x3 + x + 1 = 0
2x + 3 cos x ex = 0
2
dy
= ex
dx
y(0) = 1
Ax = B where A is a large matrix
Z
1 + cos2 x
0
What kind o
MAT3012 NUMERICAL ANALYSIS LAB EXERCISES
QUESTIONS
Problem: Test which number is greater e or e .
Problem: Calculate the sum 12 + 2 2 + 3 2 + . . . + 100 2 .
Problem: The Fibonacci sequence is given by f 1 = 0 , f 2 = 1 , and f n = f n1 + f n2
For n = 3,4
Statistics is the body of procedures and techniques used to collect, present, and
analyze data on which to base decisions in the face of uncertainty or incomplete
information.
Statistics is subdivided into descriptive and inferential.
Descriptive statisti
MAT 3026HOMEWORK ASSIGNMENT
Due Date: Friday, November 31, 2014
1. A sample of 26 offshore oil workers took part in a simulated escape exercise, resulting in
the accompanying data on time (sec) to complete the escape ("Oxygen Consumption and
Ventilation D
MAT3026  Probability and Statistics
Homework 3
Name & Surname: .
Student Number: .
Section Number: .

Note:
Print a copy of this sheet and include it as a cover page for the homework.
No typed homework will be accepted; handwritten assignments only!
Due
Definition: The set of all possible outcomes of a statistical experiment is called
the sample space and is represented by the symbol S.
Each outcome in a sample space is called an element or a sample point of the
sample space.
Example: The sample space S,
Definition: A random variable (r.v.) is a function that associates a real number
with each element in the sample space.
A random variable is called a discrete random variable if its set of possible
outcomes is countable.
EXAMPLE: The experiment is flippin
BAHEEHIR UNIVERSITY
FACULTY OF ARTS AND SCIENCES
DEPARTMENT OF MATHEMATICS
20142015 Fall Semester
COURSE CODE
COURSE TITLE
Instructor:
MAT3026
Probability and Statistics
Prof. Dr. Ali Hakan Bykl
Office:
Tel: (0212) 3834415 email: [email protected]
The Geometric Distribution
This is an example of a waiting time problem, that is, we wait until a certain event
occurs. We make the assumptions used in the binomial distribution so we assume
that:
1. on each trial of our experiment, the result is one of t
Sampling Distributions
Definition: A population consists of the totality of the observations with which we
are concerned.
Definition: A sample is a subset of a population.
Definition:
1
Definition: Any function of the random variables constituting a rando
Definition: If a sample space contains an infinite number of possibilities equal to
the number of points on a line segment, it is called a continuous sample space.
A random variable can take on values on a continuous scale, it is called a
continuous rando
Example: Seven applicants have applied for two jobs. How many ways can the
jobs be filled if
(a) the first person chosen receives a higher salary than the second?
Permutation
(b) There are no differences between the jobs?
Combination
1
Definition.
A proba
Homework Assignment 4
Due on Friday 5, December 2014
1. An important factor in solid missile fuel is the particle size distribution. Significant
problems occur if the particle sizes are too large. From production data in the past, it has
been determined t
Continuous Probability Distributions
The observations generated by different statistical experiments have the same
general type of behavior. The followings are the probability distributions that will
be covered in this chapter:
Normal Distribution
Gamma
The Binomial Distribution
Perhaps the most commonly used discrete probability distribution is the binomial
distribution.
An experiment which follows a binomial distribution will satisfy the following
requirements,
1. The experiment consists of n identical
Math 2033 (Discrete Mathematics) Syllabus, Spring 2015
I NSTRUCTOR :
E MAIL :
L ECTURES :
T EXT:
Atabey KAYGUN
[email protected]
(Section 2) Wednesdays 12:303:30 (D405)
Discrete Mathematics and Its Applications, Sixth Edition by Kenneth