1
History 152: United States from the Civil War to the Present.
Sections 07 and L02.
Spring 2016
Tues/Fri 11:10 12:00 (lectures) HW615
(Weekly discussion sections meet separately.
See last page of syllabus for section days/times)
Prof. Donna HavertyStack
Chapter 4
Conditional Probability
Example 1:
A box contains 4 balls A, B, C, and D. Two
balls are drawn, one right after the other
with replacement. Given that the same ball
does not appear on both draws, what is
the probability that neither of the 2 bal
Chapter 9
Special Discrete
Probability Models
Bernoulli Distribution
There are only two outcomes; a success or a
failure.
X = 1 a success with probability
X = 0 a failure with probability (1
Then f(x) = x (1x)
and
E(X) =
V(X) =
Binomial Distribution
STATISTICAL EXPERIMENTS
Gathering data  many ways
Socioeconomic surveys
Experiments in biology, physics, chemistry
Experiments and surveys in the health sciences
The Sample Space 1
All possible results of an
experiment, (labeled S)
Exhaustive & Exclusi
Chapter 8
Joint Probability Functions
Expectation
If X and Y have the joint p.f. given below.
Find E(XY) and E(X/Y).
E(XY) =
E(X/Y)
Covariance
When we study two random variables
simultaneously, we want to know how they vary
together or jointly. This join
Chapter 6
Random Variables
Definition: random variable
The numerical values attached to the
elements of the sample space, plus their
associated probabilities is called a
probability function, or a probability
density.
Terminology:
A set of numerical value
Chapter 5
Independence
Independence
In everyday language, we describe two events
that have nothing to do with each other as
independent.
In statistics, independence is yet another English
word with precise statistical meaning.
Independence
P(AB) = P(AB)/
Chapter 3
Counting Procedures and Their
Applications
Uniform Probability Model
When simple events in a sample space
have equal probabilities, we have a
uniform Probability model
Pr(event ) = # outcomes in E
# outcomes in S
Example:
Suppose a class consi
Chapter 7
Describing Random Variables
and Their Distributions
The Mean
Example:
# correct ans. 
# students

0 1 2 3 4 5
2 2 6 20 15 5
To compute the mean number of correct answers by
the 50 students:
0x2 + 1x2 + 2x6 + 3x20 + 4x15 + 5x5
50
= 3.18
Example
General Chemistry 2: Learning Goals
Topic 1: Equilibrium
1.
2.
3.
4.
Use molarity formula to determine moles, volume, and concentration.
Use the dilution formula to compute molarity and volume after dilution.
Write mo
Hunter College, CUNY
Chem10400
Spring 2016
General Chemistry 2: CHEM 104 Spring 2016
Lecture: Nadya KobkoLitskevitch
Email: [email protected]
Office hours: Wed 24 pm (1323N)
Goal of the course: This is the second semester of a 2semester general ch
Unformatted text preview: Names:_30 pts
total_
_ CHEM 104 Spring 2014 Workshop 10: Buffers A buffer consists of
a solution containing both a weak acid and its conjugate base. Lets try and solve some old exam
problems: (30 points)
1. Consider a 500 ml buff
2016 English Department Prizes
and Awards
Deadline for entries:
Monday, February 29, 2016
Time: 12:00 Noon
APPLICATION FOR THE 2016 ENGLISH DEPARTMENT PRIZES AND AWARDS
Deadline: 2/29/2016 at 12:00 noon
1) NAME (Mr.; Ms.): _
2) CUNY First Number: _
3) EM