HW1
1. Taylors polynomial approximating a function is defined as follows
( )
( )
(
( )
( )(
)
)
( )
( )
)
( )
( )
( )
Use the Matlab symbolic computation functions: syms x; diff(f,x,j), to derive the
derivatives manually first and then the Taylor polynom
CS 323 Homework Solutions
Due: 02/16/2015
I. f (x) = x3 + x2 1 = 0.
(i) f (0) = 1 < 0, f (1) = +1 > 0 = sign change over [0, 1] = theres a root
x [0, 1].
Uniqueness of x: follows from fact that f (x) is an increasing functions of x (f 0 (x) =
3x2 + 2x > 0
Dividend and Payout Policy
Xin Cheng
Outline
Dividend Payments
Dividend Theory
Does Dividend Policy Matter?
Factors Favoring a Low Dividend Payout
Factors Favoring a High Dividend Payout
Experience with Dividend Policies
Rutgers Business School
2
Di
Data Structures Review
Session 1
Ramakrishna, PhD student.
Grading Assistant for this course
CS 307 Fundamen
1
Java exercises
For the following program, what are the possible
outputs ?
Public class WhatIsX
cfw_
public static void f(int x)
cfw_
/* body un
Errors and more practice problems
We start with an interval
cfw_(
)(
)
, a function
and +1 points in that interval
(
) and find a polynomial
. We
 for all points in the given interval. As we increase the
want to find the error 
distance between two cons
HW2
1. Matlab functions realmax('double'), intmax('int64'), realmax('single'), intmax('int32') give the
IEEE maximum Real and integers and eps('double'), eps('single') give the smallest representable
Real numbers that can be represented in 64 and 32 bit
Financial Modeling
Chapter 2
What are the components of a
model?
Ben J. Sopranzetti, Ph.D.
1
Parts of a model getting
started
Balance
Income
Sheet
Statement
Statement
of Cash Flows
Ben J. Sopranzetti, Ph.D.
2
Two kinds of models
Forecasting Model
Trans
HW6
1.
Another form of the error for Trapezoidal rule can be given by The General Euler
McLaurin formula is defined by ,
() = ( ) + 1 () + ()
=0
=1
2 2 (21)
() (21) () +
(
(2)!
Where the Bernoulli numbers are given by
1
1
1
1
1
1 = 2 , 2 = 6 , 3 = 0,
Readme file
Nishtha Sharma
Hiren Patel
Election Final Project 336

Our project is Senator Voting Record Database. It grabs information
a citizen may want to know about their senator and how they vote on
particular bills. It helps agregate data which wou
README
Hiren Patel hkp35
Kapil Srinivas Jayaraman kj184
The goal of this assignment was to create a program that allows us to compare multithreading and
multiprocessing. To compare the similarities and differences we used a RLE algorithm to compress
str
Kapil Srinivas Jayaraman kj184
Hiren Patel hkp35
Timing and Analysis
The purpose of this analysis is to witness and comprehend the performance similarities and differences
between the thread and process version of the modified RLE compression. Each sectio
waht is objective of database design?
avoid redundancys and update anomolies
there are more superkeys than keys
Lamar Alexander (RTenn.): $23,426
Kelly Ayotte (RN.H.): $7,450
John Barrasso (RWyo.): $21,489
Roy Blunt (RMo.): $1,439,902
John Boozman (R
8. Trading Strategies
We can use options to produce an
interesting relationship between
profits and stock price
Intuition
Lego games
1
Trading Strategies
Take positions in:
The option and the underlying asset
Two or more options of the same type
 spread
function [ result ,error] = taylor( z,a,n )
syms x real;
0=exp(x)*sin(x);
f=exp(x);
sum=subs(f,'x',a);
prod=1;
for j=1:n
prod=prod*(za)/j;
sum=sum+prod*subs(diff(f,x,j),'x',a);
end
format long
result=double(sum);
error=double(abs(resultsubs(f,'x',z);
en
SOLVING LINEAR SYSTEMS
We want to solve the linear system
a1;1x1 +
an;1x1 +
+ a1;nxn = b1
.
+ an;nxn = bn
This will be done by the method used in beginning
algebra, by successively eliminating unknowns from
equations, until eventually we have only one equ
HW4
1. The following Program computes the L and U decomposition of a matrix i.e A=LU using a
rowwise access of the data. If we interchange the loops i with j, we get the wellknown
columnwise access LU decomposition, also known as the kji form.
i.
Writ
function root = newton(x0,error_bd,max_iterate,index_f)
%
% function newton(x0,error_bd,max_iterate,index_f)
%
% This is Newton's method for solving an equation f(x) = 0.
%
% The functions f(x) and deriv_f(x) are given below.
% The parameter error_bd is u
function root = iteration(x0,error_bd,max_iterate,index_f)
format short e
error = 1;
it_count = 0;
while abs(error) > error_bd & it_count <= max_iterate
gx = g(x0,index_f);
%
%
x1 = gx;
error = x1  x0;
Internal print of newton method. Tap the carriage
re
Management Skills
Team Project Description and Assignments
Description: This project is designed to promote your analytic and critical thinking skills; to
encourage application of our course concepts to realworld organizations; and to develop your
interp
Customer Relationship
Management Group
been,
Groom
My
Pet
Your companyExercise
Groom My Pet has
and continues
to grow
very
rapidly. You now have over 340 franchisees in all 50 US states plus 23
locations in Canada. There are 620 store locations and 973 M
function [ xnext] = falseposition( a,b,tol)
xnext=a(ba)*f(a)/(f(b)f(a);
while abs(f(xnext)>tol
if f(xnext)*f(b)<0
a=xnext;
else
b=xnext;
end
xnext=a(ba)*f(a)/(f(b)f(a);
end
end
function val=f(x)
val=x^21;
end
PageRank  Page, Brin (1998)
View web as directed graph G
 nodes of G represent web pages cfw_P1 , ., Pn; n 1 trillion = 1012 .
 edges of G denote links from one web page to another.
Example 1:
n = 4, edges: cfw_12, 24, 31, 32, 34, 43
Random walk experi
CS 323 Computer Problem: Polynomial Interpolation  due 4/15/15
Write a Matlab function
function fz = interp(x,f,z)
which takes vectors x, f of data points:
(x1 , f1 ), (x2 , f2 ), ., (xn+1, fn+1 ),
determines the corresponding interpolating polynomial pn
CS 323 Homework  due 2/4/15
I. On a machine which rounds and has floating point numbers characterized by = 10,
n = 5, m = 40, M = 40:
(i) How would the following numbers be approximated: (a) 6.0221367 1023 (Avogadros number) (b) 9.1093897 1028 (the mass
——_ﬁﬂ.—_4
QU 3 Last Name  «First Name  
1. We want to solve Ax=b. Solve the system by using Gaussian elimination with pa rtiai pivoting for
3 1 0 3
14:1 3 1. ll: 0
O 1 2 —2
the following linear systems:
i. What is the one norm “All1 =
\0 ii. What is t
\O‘h‘x quz. L .
QU '2‘ 1 LastNamemFirstName
1. Taylor’s polynomial approximating a function is defined as follows
_ n fUJ(a)(x 601'
Pntx) —f(a)
nx — (n+1)! f , a_x_ﬁ,an a_,u_x.
f (x) = Pan) + Rn(x)‘
i. Find the Taylor’s polynomial and error for f(x) =