STOR 435
Semester: Fall 2014 Exam: Practice Midterm #2 Time: 75 minutes Total Points: 45
Instructions: There are 9 questions each worth 5 points for a total of 45 points.
Do not focus only on these pr
STOR 435 Exam 2 Summer Session II 2013
Name:
ID#:
1 pledge that I have-neither given nor received unauthorized aid on this exam.
Signature:
(1) Check “true” or “false”.
(3.) If X N Uniform (—a,e), Y N
STOR 435
Supplementary Problem Set 1
(1) let X N (, 2 ), P (X 0) = 1/3 and P (X < 1) = 2/3. Find P (X > 2).
(2) Let X N (1, 4), A = cfw_0.4 < X 2.4 and B = cfw_1.2 X < 7. Find P (A B ),
P (A B ), P (A
STOR 435.001 Semester: Spring 2017 Homework 4 Total Points: 20
Instructions: Number of points for each problem are displayed on the right in boxes.
Problems 1-5 have no partial credit so just write do
STOR 435.002 Semester: Spring 2015 Homework 7 Total Points: 16+4
Instructions: 4 points for completion of all problems.
Due Date: March 25 [Wed], 2015.
There is no difference between the 8th and 9th e
STOR 435.002 Semester: Spring 2015 Homework 4 Total Points: 16+4
Instructions: 4 points for completion of all problems.
Due Date: Feb 4 [Wed], 2015.
There is no dierence between the 8th and 9th editio
STOR 435.002 Semester: Spring 2015 Homework 5 Total Points: 16+4
Instructions: 4 points for completion of all problems.
Due Date: Feb 25 [Wed], 2015.
There is no dierence between the 8th and 9th editi
STOR 435.001 Semester: Fall 2014 Homework 4 Total Points: 20
Instructions: Number of points for each problem are displayed on the right in boxes.
This is your final HW 4, no more questions will be add
STOR 435.001 Semester: Fall 2014 Homework 11 Total Points: 20
Instructions: Number of points for each problem are displayed on the right in boxes.
More questions will be added on Thursday.
Due Date: N
HOMEWORK 1 SPECIAL PROBLEMS
[Special Problem] 1. A tourist wants to visit 5 of Americas 12 largest cities. In how many
ways can she do this if
(a) The order of her visits is important.
(b) The order o
Probability Exam
July 2014 Syllabus with Learning Objective/Outcomes and Readings
The Probability Exam is a three-hour exam that consists of 30 multiple-choice questions and is
administered as a compu
Lecture 21: Conditional Density and Expectation
STOR 435, Fall 2015
11/12/2015
435-Fall-2015
conditional density
Motivation and Definition
Pitman: Sections 6.3
Subtlety: Suppose (X, Y) has a join dens
Common Continuous Distributions
The Uniform Distribution
Definition: the Uniform Distribution has a constant (uniform) pdf from a to b.
1
Probability Function: f ( x)
b a
x a
Distribution Function: F
EDUCATION AND EXAMINATION COMMITTEE OF THE SOCIETY OF ACTUARIES
RISK AND INSURANCE
by Judy Feldman Anderson, FSA and Robert L. Brown, FSA
Copyright 2005 by the Society of Actuaries
The Education and E
Quadratic Formula
Given: ax 2 bx c 0
Solve for x: x
b b 2 4ac
2a
Square of a Sum
(a b) 2 a 2 2ab b 2 and
(a b c) 2 a 2 b 2 c 2 2ab 2bc 2ac
Series Formulas
Geometric Series: a, ar, ar2, ar3, a + ar +
Exam. 1, Stat 435, Section 11 Fall 2006
Name:
' This exam consists of 9 questions. To receive partial credit you must show
all work.
1. (5 points.) An urn contains 12 balls of which 4 are white. Three
Lecture 16: Independent Normal Random Variables
STOR 435, Fall 2015
10/20/2015
435-Fall-2015
independent normal
Facts and Example 1
Pitman: Section 5.3
Facts:
If X = Z + with parameters IR and > 0, th
Exam.
1, Stat 435, Section 1, Fall 2007
Name:
This exam consists of 9 questions. TvIaximum points:
credit you must show all work.
60. To receive
partial
1. (6 points.)
An experiment consists of first
Lecture 15: Uniform Distributions
STOR 435, Fall 2015
10/13/2015
435-Fall-2015
multivariate uniform
volume proportion
Pitman: Section 5.1
A random vector (X1 , ., Xn ) is said to be uniformly
distribu
Lecture 19: More on Covariance and Correlation
STOR 435, Fall 2015
11/5/2015
435-Fall-2015
more on correlation
Definition and properties
Pitman: Section 6.4
Example 1: (similar to Lecture 8, Example 4
Lecture 13: CDF
STOR 435, Fall 2015
10/8/2015
435-Fall-2015
cdf
CDF
Pitman: Section 4.5
Definition: F(x) = P(X x), x IR. Every RV X has a cdf,
regardless of its type: discrete, or continuous, or other
Lecture 11: Density and Expectation
STOR 435, Fall 2015
9/29/2015
435-Fall-2015
density and expectation
HG to density curve
Histogram vs Density Curve
435-Fall-2015
density and expectation
density
Pit
Lecture 17: Transformations
STOR 435, Fall 2015
10/29/2015
435-Fall-2015
transformation
Facts and Example 1
Pitman: Section 5.4
Note: Special care is required in performing multiple
integration with s
Distribution of Continuous Random Variables
Name
density (pdf )
distribution (cdf )
Exponential
Normal
f ( x) =
1
e
2
Pareto
f ( x) =
Gamma
f ( x) =
f ( x) =
(+ ) 1
(1
()( ) x
Lognormal
f ( x) =
1
STOR 435 Exam 1 Summer Session I 2015
Name: MIMI-H W f
ID#:
I pledge that I have neither given nor received unauthorized aid on this exam.
Signature:
(1) Check true or false.
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Lecture 18: Covariance and Correlation
STOR 435, Fall 2015
11/5/2015
435-Fall-2015
correlation
Definition and properties
Pitman: Section 6.4; also see Lecture 8 for the definition.
Covariance:
Cov(X,
Lecture 20: Conditional Distribution and Expectation:
Discrete Case
STOR 435, Fall 2015
11/12/2015
435-Fall-2015
conditional expectation
Basics
Pitman: Sections 6.1 and 6.2
Denote the sets of atoms fo
Lecture 12: Exponential and Gamma Distributions
STOR 435, Fall 2015
9/29/2015
435-Fall-2015
exp and gamma
Exponential distribution
Pitman: Section 4.2
Let lifetime X Exp() with density f (x) = ex , x