Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Math 19a
Name
Modeling and Dierential Equations for the Life Sciences
Second Practice Exam IFall 2012
Guidelines for the test:
No books or calculators are allowed, but you may use one 4 6 index card (front and
back) of notes.
You may leave answers in sy
Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Problem Set 4
Math 19b
Spring, 2012
Due in lecture Wednesday, February 22.
Turn in solutions to each of the following problems.
1. Taubes Problem 6.1
2. Taubes Problem 6.3
3. Taubes Problem 6.4
4. Taubes Problem 6.5
5. Suppose X and Y are two random varia
Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Math 19a
Mathematical Modeling
Project Description
John Hall
Fall 2012
Project Description
Your assignment is to either explain, critique, and extend a mathematical
model presented in a journal article, or formulate and analyze a model of
your own for a s
Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Math 19b
Syllabus
Instructor: Peter M. Gareld ([email protected])
Spring, 2012
Science Center 422
Course Assistant: John Capodilupo ([email protected])
The subject: This is a course on linear algebra, probability and statistics, with
Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Normal or Canonical Forms
Rosen 1.2 (exercises)
Logical Operators
 Disjunction
Do we need all these?
 Conjunction
 Negation
 Implication pq p q
 Exclusive or (p q) (p q)
 Biconditional p q
(pq) (qp)
(p q) (q p)
Functionally Complete
A set of log
Modeling and Differential Equations for the Life Sciences
MATH 19

Spring 2012
Point Estimates:
Para Esti Formula
meter mate
0
0
0 = y 1 x
Expected Value Variance of estimate
0
2 x2
nS xx
=
2 x2
(
n x x
2
1
x
= +
n x x
2
(
1
1
1
S xy
S xx
(y y )(x x )
=
(x x )
i
i
2
i
=
n xy x y
n x 2 ( x )
2
xy
x y
=
x
2
n
( x)2
n
2
S xx
=
E