Part 1
1. Continuous distributions:
a. Use mean command to nd the sample mean x of these data:
Mean of C1 = 4.99480
b. What is the mean of the uniform distribution on the interval [3,7]:
Use formula from class
c. Compare to the value x you found in part a

Lecture 10
Ch. 4 Section 4.3-4.5
Examples of binomial
experiment
Number of girls in a family of 4 children
Number of international students in a
sample of 10 students.
Number of laser jet printers in 40 printers
used in Math department.
Number of Mostly s

Lecture 14
Ch. 6. Sampling
distributions
Sampling distribution for sample
mean
Example1
Example 2: Fuel efficiency
A midsize car model maker claims that its
mean fuel economy (MFE) is less than
7.6L/100km (and therefore entitled to a tax
credit). Lets che

Lecture 13
The exponential
distribution
Relation to Poisson distribution
Formulas
Another example
Patients arrive at a hospital emergency
room according to a Poisson distribution.
Records show that on average, 7 minutes
elapse between two successive arriv

Lecture 8
Ch. 3 (Cont)
Multiplicative rule
An other example
Example 2: A dryer and a washer
independently work properly with
probability .95 and .85 (respectively).
What is the probability that (a) both
machines work properly? (b) none of them
works prope

Lecture 2
Week 2
Finish Chapter 1
Brief Intro to Survey methods
Survey is a questionnaire: specific variable
Examples: Likart scale for job satisfaction,
or StatCan surveys.
Purpose of a survey: get responses from
participants.
Four Steps: 1 decide upon c

Lecture 12. Ch. 5 (Cont)
More examples on
normal distribution
One more example on normal
distribution: Stocking energy
Weekly demand at rink for a brand of
d a store
energy drink is approximately normally
distributed with mean of 1,000 cans, and
standard

Lecture 4
Ch 2 (Continued)
How to interpret standard
deviation
q
Small std little variability between data
Big std large variability (spread)
between data.
Example: Compute std for and compare
hourly wages and revenue data (see
minitab)
The normal curve (

Lecture 9
Ch. 4 Discrete random
variables
Examples
A discrete random variable (RV) is a count
variable. For example:
Number (out of 10 injured ) who will need
to stay in a local Ottawa general hospital.
Rating on 1-5 scale of a prof by a student.
Number o

Lecture 6
Ch 2 (end of ) and
beginning of Ch. 3
Describing qualitative data
Pie chart and bar chart.
Example: Canadian forces distribution per
province and overseas (OS). (See
minitab file for data: province and
employee variables) (Some territories are
o

Lecture 7
Ch. 3 (Cont).
Example on Union rule
At a Canadian university, professors come
from different places of the world. The
following is a distribution table of Math/stat
department professors according to their
provenances (PhD defenses country):
Cou

1. a) 6/10 = 0.6
b) 44/100 = 0.44
c) 5054/10000 = 0.505
d) Part c is closest to 0.5
e) If you could flip the coin an infinite number of times, the value would be 0.5
2. a) 12/36 = 0.33
b) 18/36 = 0.5
c) P (CD) = 6/36
d) P (C|D) = 6/18
e) The conclusion ab

Minitab Project Report
Part A
Hi st ogr a mof C1
Hi st ogr a mof C1
20
10
8
Fr e que ncy
Fr e que ncy
15
10
5
6
4
2
0
10
0
10
C1
20
0
30
10
0
10
20
C1
30
Hi st ogr a mof C1
10
Fr e que ncy
8
6
4
2
0
12
6
0
6
C1
12
18
24
30
One of the biggest difference

Lecture 3
Week 2
Chapter 2
Describing shape of a
distribution
Stem-and-leaf: main unit is stem, so that
there will be 5 to 20 stems. Subsequent
unit is leaf.
Example 1: GPA data.
Histogram (or frequency histogram): data
divided into classes, the bars heig