Read assignments before
class. Review notes from previous classes regularly.
Number each exercise to the
left.
Work only one problem across the page -- i.e. problems should proceed form top
to bottom.
You must show your work! Correct mathematical notation must be
used. Partial credit is given when work is shown even if answer is
incorrect. However, correct answers without any work shown will in general
be given no credit.
If the problem is a computation leading to a final answer, box the answer.
Use pencil and eraser -- do not scratch out work.
Start homework early and
see me for help with problems you don't know how to work! It is
inappropriate to ask how to do a problem in class the day it is due!!!! Staple
your pages together before submitting. My office is Core 257-- See my schedule for office
hours or call or send email for an appointment. I am always delighted to help.
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Date |
Exams or Quizzes |
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Reading Assignments |
Assignments Due -- Tentative
– Will adjust as necessary |
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Mon. 8l/24 |
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Wed. 8/26 |
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Section
1.2 |
Read
section 1.1 for your own interest only. In Section 1.2, we focus on learning
terms and definitions and Venn Diagrams, While a nice example of
proof, you are not responsible for example 1.8 of section 1.2 |
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Fri. |
|
Sections
1.3, 1.4 |
The three
probability axioms and statements of the resulting three theorems in section
1.3 and examples are important. Results from section
1.4 (theorems and corollaries) will be used over and over in this
course! |
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|
Mon. |
|
Sections 1.5, 1.6, 1.7 |
You may
skip sections Section 1.5, 1.6 and 1.7 or read lightly – skipping formal
arguments. Know main points that I discuss in class about selecting
points at random from an interval (uniform distribution). |
Set
1: Section 1.2 |
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Wed. |
|
Sections
2.1, 2.2, 2.3 |
In
Section 2.2 we are dealing with the counting principle ( the product rule for
counting) with applications to some important examples. Section 2.3
deals with permutations (ordered arrangements of objects) |
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Fri. |
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Section
2.4 deals with combinations (unordered selections of objects). |
Set
2: Section 1.4 Set
3: Section 1.7 and Review ex. |
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Mon. |
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|
LABOR DAY
NO CLASS |
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Wed. |
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Section
2.4 Section
3.1 |
Section 2.4
deals with combinations (unordered selections of objects). In
Section 3.1, look at the conditional probability of an event given that
another event has occurred |
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|
Fri. |
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|
Covers: Def of Sample space, event, prob. Axioms,
Principle of Inclusion Exclusion, Product Rule, Permutations, Combinations,
Conditional Probability Formula |
Set 5 |
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Mon. |
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|
Set
6: Section 2.4 |
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Wed. |
|
Section
3.2 |
We
rearrange the conditional probability formula to obtain the Law of
Multiplication |
Set
7: Section 3.1 |
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Fri. |
Quiz |
Section
3.3 |
The Law
of Total Probability that allows us to calculate the probability of an event
A using P(A|B) and P(A|Bc). |
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Mon. |
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Section
3.4 |
Baye’s
Formula |
Set
8: Section 3.2 |
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Wed. |
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Section
3.5 |
|
Set 9: Section 3.3 |
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Fri. |
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Section
4.1 |
Random
Variable |
Set
10: Section 3.4 |
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Mon. |
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Set
11: Section 3.5 |
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Wed. |
Exam 1 |
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Fri. |
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Section
4.1 |
Distribution
function of a random variable |
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Mon. |
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Section
4.2 |
Defining
concept of random variable and its distribution function |
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Wed. |
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Section
4.3 |
Definition
of a random variable's probability function. |
Set
12: Section 4.1, 4.2 |
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Fri. |
|
Section
4.4 Section
4.5 |
Expectation
of a random variable. Variance
and Moments of random variables. |
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Mon. |
|
Section
4.6 Section
5.1 |
Standardizing
a random variable Bernoulli
and Binomial random variables; Binomials, calculating related probabilities,
expected values and variances. |
Set
13: Section 4.3 Set
14: Section 4.4 |
|
Wed. |
Quiz Topics |
Section
5.2 |
Poisson
random variable. Using it to approximate binomial random variables.
Definition and properties of a Poisson process. Probability function
formula for Poisson random variable. |
Set 15: Section 4.5 and 4.6 |
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Fri |
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NO CLASS
-- MID TERM BREAK |
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Mon. |
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Wed. |
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Section
5.3 |
Other
discrete random variables: Geometric, hypergeometric, and negtive
binomial random variables |
Set
16: Section 5.1 |
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Fri. |
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Set 17:
Section 5.2 |
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Mon. |
|
Section
6.1 |
Continuous
random variables, density function for continuous random variable.
Relationship between density and distribution function. Calculating
various probabilities from each |
Set
18: Section 5.3 |
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Wed. |
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Fri. |
Exam 2 |
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|
Set 19:
Section 6.1 |
|
Mon. |
|
Section
6.2 |
Through
example 6.5. Computing distribution function and density function
of a function h(X) from the density of random variable X. |
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Wed. |
|
Section
6.3 |
Computing
expectation, variance and standard deviation of continuous random variables. |
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Fri. |
|
Section
7.1 |
Uniform
random variables |
Set 20:
Section 6.2 |
|
Mon. |
|
Section
7.2 |
Normally
distributed random variables; approximation to binomial distribution. |
Set 21:
Section 6.3 |
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Wed. |
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|
Set 22:
Section 7.1 |
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Fri. |
|
Section
7.3 |
Exponential
distribution. Density, relationship to a Poisson process |
Set 23:
Section 7.2 |
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Mon. |
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Wed. |
|
Section
8.1 |
Bivariate
Distributions |
Set 24:
Section 7.3 |
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Fri. |
|
Sections
8.2 |
Independent
Random Variables |
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|
Mon 11/23
– Fri 11/27 |
|
|
THANKSGIVING
BREAK -- No Class |
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|
Mon. |
|
Section
10.1 |
Expectation of sums of random
variables. Indicator random variables. |
Set 26:
Section 8.1 |
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Wed. |
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Set 27:
Section 8.2 |
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Fri. |
Exam 3 |
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|
Set 28
Section 10.1 |
|
Mon. |
|
Sections
10.2, 10.3 |
Covariance
and Correlation of jointly distributed random variables. Variance
of sums of independent random variables. |
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Wed. |
|
Section
11.5 |
Central
Limit Theorem -- applications |
Set 29:
Section 10.9 |
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Fri. |
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Set
30: Section 11.5 |
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Tues. |
|
Final
Exam |
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|
Set Number |
Written Problem Assignments |
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1 |
Section
1.2: 2, 5, 6, 7, 9, 10 -- draw Venn Diagrams for these also , 11 |
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2 |
Section
1.4: 1, 2, 3, 4, 5, 6, 8, 12, 16, 18, 22, 26 |
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3 |
Section
1.7 2, 4, 5, 10 and Review Exercise 10, page 36. |
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4 |
Section
2.2 2, 4, 5, 6, 7, 8, 10, 15, 18 |
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5 |
Section
2.3 1, 2, 4, 6, 9, 10, 12, 18, 21 |
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6 |
Section
2.4 1, 2, 3, 4, 5, 6, 7, 15, 16, 18, 22 |
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7 |
Section
3.1 2, 4, 7, 8, 9, 16 |
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8 |
Section
3.2 2, 4, 6, 8 |
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9 |
Section
3.3 1, 2, 3, 4, 6 |
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10 |
Section
3.4 1, 2, 3, 6, 8 |
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11 |
Section
3.5 1, 3, 4, 6, 8, 12, 15, 22 |
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12 |
Section
4.2 1, 2, 5, 10, 11 |
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13 |
Section
4.3 1, 2, 4, 7, 8 |
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14 |
Section
4.4 2, 3,4, 5, 6 |
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15 |
Section
4.5 1, 2, 4, 6, 7, 8; |
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16 |
Section
5.1: 1, 2, 6, 9, 10, 13, 18 |
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17 |
Section
5.2: 1, 2, 4, 5, 6, 11, 12, 14, 16 |
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18 |
Section
5.3: 1, 3, 4, 5, 8, 13, 16 |
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19 |
Section
6.1: 1, 2, 5, 8 |
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20 |
Section
6.2: 1, 2, 4, 5 |
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21 |
Section
6.3: 1, 2, 4, 8, 9 |
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22 |
Section
7.1: 1, 2, 4, 5, 10 |
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23 |
Section 7.2: 1, 2, 6, 8, 9, 10 |
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24 |
Section
7.3 1, 2, 3, 4, 5, 7 |
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26 |
Section
8.1: 1, 2, 3, 6, 9; |
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27 |
Section
8.2: 1, 2, 9, 11 |
|
28 |
Section
10.1: 4, 5, 12 |
|
29 |
Section
10.2: 2, 3, 18 Section
10.3 1, 2 |
|
30 |
Section
11.5: 1, 2, 3, 6 |