Tutorial 3
29th/ 31st Jan 2014
Question 1:
A survey by Gallup asked a random
sample of American adults about their
soda consumptions. Let X represent the
number of glasses of soda consumed on a
typical day. Gallup found the following
probability model for
STAT 202, Fall 2014
Assignment 1
Due: Wed, Oct 1st 2014, by 5pm
First Name:
Last Name:
Student Number:
Section Number:
001
002
Acknowledgments:
Instructions:
Fill in the top part of this title page and use it as a cover page for your assignment;
Clea
Lecture 10
28th Jan 2013
Question:
It is known that 70% of the time you bike to
class, and 30% of the time you take the
bus. If you take the bus to class in the
morning there is a 20% chance youll
arrive late. When you go by bicycle there
is a 10% chance
Density Curves (Section 3.4)
Often, as we previously saw, it is desirable
to visualize a data set by plotting a relative
frequency Histogram.
In some cases, especially when the variable
is continuous, the frequency distribution
can be represented by a s
Lecture 9
25th Jan 2013
Example:
A study of consumer smoking habits
include 200 married people (54 of whom
smoke), 100 divorced people (38 of whom
smoke), and 50 adults who never married
(11 of whom smoked). Out of those who
were married, what percentag
Lecture 2
Jan 9th
Review:
Analysis Techniques
1.Graphical techniques (visual
representation of data)
Example:
Consider the following data:
1,2,2,3,3,3,4,4,4,4,5,5,5,6,6,7
One graphical technique is to build a
display of the data by simply ticking off
eve
Lecture 8
23rd Jan 2013
Mutually Exclusive
Two events are mutually exclusive
(ME) if they have no outcomes in
common or can never occur
together.
Is the event A person wears glasses
mutually exclusive from the event A
person has brown eyes?
A.Yes
B.No
E
Lecture 13
4th Feb 2013
Example
The number of celery seeds that germinate
in a packet of 5 seeds has the following
cdf:
X
0
1
2
3
4
5
F(x)
0.1
0.2
0.3
0.5
0.8
1
Questions follow.
What is the probability that less than 2
seeds germinate?
X
0
1
2
3
4
5
F(
Lecture 3
th
Jan 11 2012
Order Statistics (Section 2.4)
Recall we represented the Median by
Q2 and said that it is called the Second
Quartile.
The Median actually represents one of
3 quartiles that we will talk about.
A quartile derives its name from
quar
Lecture 12
1st Feb 2013
Wording
If we say that our answer is at most 4, then
our answer can
A)Include 4
B)Not include 4
Notation:
If we say that our answer is at least 4,
then our answer can
A)Include 4
B)Not include 4
Notation:
If we say that our answ
Lecture 7
21st Jan 2013
Classical
The probability of some event/ outcome
is:
Number of ways the event can occur
Number of outcomes in S
Assumes that all points in S are
equally likely
Probability
Let E be an event containing |E| simple
outcomes.
Let S be
Lecture 6
18th Jan 2013
Stem and Leaf Plots
Recall that when we draw a boxplot or a
histogram the individual data values are lost.
The Stem and Leaf plot attempts to fix this
issue.
The plot consists of two mains
parts/components; the Stem and the Leaf
E
Lecture 10
29th Sept 2014
Potential Questions of Interest?
Recall the rabbit experiment
What if we want to know the probability
that we select either a brown OR a
mottled rabbit?
We want to know the probability that in 2
tries we select a brown AND a mott
Lecture 7
22nd Sept 2014
Examining Relationships
Between Variables
Problem: Do people who attend a diabetes
control class manage their blood glucose levels
better than those that received individual
instruction?
What are a few things that we observe when
Mutually Exclusive
Two events are mutually exclusive
(ME) if they have no outcomes in
common or can never occur
together.
Is the event A person wears glasses
mutually exclusive from the event A
person has brown eyes?
A. Yes
B. No
Examples of ME events:
Tetrapods II - Endotherms
Aves and Mammalia
Ectothermy and Endothermy
Ectotherm an animal that derives its body heat primarily from the
environment. Body temperature can vary widely.
body temperature can be partially regulated behaviourally, by basking
a
Lecture 26
th
11 Nov 2016
Continuous Random Variables
Let X be a continuous random variable then:
Probability Density function (PDF)
= =
Properties:
1.
= 1
2. Mathematically this exists, however for a
continuous r.v = = = .
Why?
Recall for Conti
Lecture 19
th
26 Oct 2016
Lecture Outline:
Recall
Random Variables, Probability Function
Find the Prcfw_Diameter<8
A) [0;20)
B) [20;40)
C) [40;60)
D) [60;80)
E) [80;100)
Determining Mean and Median
Median: value that the divides the area under the
cu
Lecture 17
st
21 Oct 2016
Lecture Outline:
Recall
With vs. Without Replacement
Risk and Odds
Question:
Among those people who are infected with a certain
virus, 32% have strain A, 59% have strain B, and the
remaining 9% have strain C. Furthermore, 2
Lecture 22
st
1 Nov 2016
Lecture Outline:
Recall
Binomial Distribution
Poisson Distribution
Physical setup:
An experiment where:
Two outcomes: Failure and Success
Independent trials
Multiple trials: repeat the experiment more
than once, i.e have
So far our discussion has been around calculating
probabilities for simple and compound events
defined from a Sample Space.
Recall: This Sample Space (set of all possible
outcomes) is defined based on the Experiment
(random phenomenon) being done.
Inst
Examining Relationships Between Variables
In the blood glucose data we were looking to see
whether our response variable: fasting blood
glucose level, differs across the two levels of the
explanatory variable (in-class vs. individual
instruction) i.e we
Lecture 18
th
24 Oct 2016
Sampling Without Replacement
Consider a population of potato sacks, each of
14 potatoes, and all the values are equally
I randomly select two sacks WITHOUT
replacement and for every selection I make a
note of number of potatoes
Lecture 13
th
7 Oct 2016
Lecture Outline:
Recall
Mutually Exclusive and Independent Events
Solving for Unions and Intersections
Mutually Exclusive
Two events are mutually exclusive
(ME) if they have no outcomes in
common or can never occur
together.
Lecture 20
th
28 Oct 2016
Lecture Outline:
Recall
Plotting the p.f and c.d.f
Example:
Rolling a die: Let X = # obtained when we roll a die.
( = )
1
1/6
2
1/6
3
1/6
4
1/6
5
1/6
6
1/6
Suppose a fair coin is tossed 3 times. Let
X=Total number of heads