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ST 371 (IV): Discrete Random Variables
1
Random Variables
A random variable (rv) is a function that is deﬁned on the sample space of
the experiment and that assigns a numerical variable to each possib
ST 371 (VII): Families of Continuous
Distributions
1
Normal Distribution
The family of normal random variables plays a central role in probability
and statistics. This distribution is also called the
ST 371 (III). Conditional Probability and
Independence
1
Conditional Probability
In this section, we are interested in answering this type of question: how the
information “an event B has occurred” aﬀ
ST 371 (VI): Continuous Random Variables
So far we have considered discrete random variables that can take on a
ﬁnite or countably inﬁnite number of values. In applications, we are often
interested in
ST371 (I). Basics of Probability
1
What is Probability
Much of what occurs in life involves situations where we are uncertain about
what is going to happen. Probability is a mathematical model for qua
ST 371 (V): Families of Discrete
Distributions
Certain experiments and associated random variables can be grouped
into families, where all random variables in the family share a certain structure and
ST 371 (II). Calculating Probabilities
1
Sample Spaces Having Equally Likely Outcomes
For many experiments, it is natural to assume that all outcomes in the
sample space are equally likely to occur. T
HW12
3
4 (parts a and e* only)
20 (part a only; calculate both the large sample confidence interval and the score interval)
37 (part a only)
Homework Page 1
1) Use the summary measures from problem 10.5 to create an ANOVA table (note: the pvalue for the factor of interest
is 0.196); also draw a welllabeled picture of the pvalue.
2) Consider the informa
ST 371 (VIII): Theory of Joint Distributions
So far we have focused on probability distributions for single random variables. However, we are often interested in probability statements concerning
two
ST 371 (IX): Theories of Sampling
Distributions
1
Sample, Population, Parameter and Statistic
The major use of inferential statistics is to use information from a sample
to infer characteristics about
9/18/2014
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CronGie Catr 14
The lecture on 2/8/2011 mainly focused on independence.
Two events A and B are independent if P(AB)=P(A) and are dependent otherwise.
If two events are independent then they cannot be mutually exclus
Joel Anderson
ST 371002
Lecture Summary for 2/15/2011
Homework 0
First, the definition of a probability mass function p(x) and a cumulative distribution function
F(x) is reviewed:
Graphically, the dr
Brent Clayton
Homework #0
Summary of class notes 2/3/2011
The lecture notes for this particular day a centered on sections 2.42.5 in the Devore book.
Basically the idea of conditional probability is
Morgan Carter
February 1, 2011
ST37102
Professor Smith
Class Summary
Review from last session:
n
n!
=
n = n1 + n 2 + .+ n k
n1,n 2 .n k n1!n 2!.n k! where
Th
9/18/2014
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Itouto t PoaiiyadDsrbto Ter
nrdcin o rbblt n itiuin hoy
SPRING
2011
STATISTICS
S3102
T70
I s r c o :D . C E S i h 4 4 S S H l , P o e 5 5
HW3
Sunday, February 5, 2017
12:18 PM
5 (Note: the pvalue for the factor of interest is 0.104)
17 (part a only); a partially completed ANOVA table for this problem is:
DF
SS
MS
F
pvalue
Sand
0.065
Homework 4
Problem 1 (based off of 10.5)
From the information provided, . . = 1.5367
Source
Treatment
Error
Total
DF
2
27
29
SS
0.2286
1.782
MS
0.1143
0.0660
Fstatistics
1.73
pvalue
0.196
MS
7.83
2.
HW 3 ST 371 Spring 2011 Due Feb. 15, 2011
Problem 1: The table below shows the number of students that fall into each of several
categories. One student will be selected at random in a raffle, and wil
ST 371 Spring 2011
1. p 155 # 36
2. p 155 # 44
3. p 156 # 50
4. p156 # 54
5. p. 162 # 60
6. p. 162 # 66
7. p. 168 # 72
8. p. 169 # 76
9. p. 169 # 82
10. p. 169 # 84
HW 6 due March 29
Problem 8: text p 76 # 68
Define events A1, A2, and A3 as flying with airline 1, 2, and 3, respectively. Events 0, 1, and 2 are 0, 1, and 2 flights
are late, respectively. Event DC = the event that th
HW 3 solutions:
Problem 1: The table below shows the number of students that fall into each of several
categories. One student will be selected at random in a raffle, and will be given a new laptop PC