COMM 291
Midterm Review Package
Prepared by Chen Qian
1
1. INTRODUCTION TO DATA AND VARIABLES
Categorical Data: Answering questions or descriptive response
Quantita

PRACTICE QUESTIONS FOR
THE MIDTERM EXAM
Part A.
Midterm Exam 2013
Midterm Exam 2012
Midterm Exam 2011
Midterm Exam 2010
Questions, Answers and Explanations
Part B.
Past Years Midterm Exams
Questions, Answers and Explanations
1
Part A. Midterm Exam 2013
No

UNIVERSITY OF TORONTO
Faculty of Arts and Science
APRIL 2007 EXAMINATIONS
ECO220Y1Y
PART 1 OF 2
Duration - 3 hours
Examination Aids: Calculator
Last
Name:
S
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T
I
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N
S
(1) (a) Solution:
pW
130
200
0.65, pM
(0.65 0.587) 1.96
88
0.587
150
0.65 (1 0.65)

Final Exam 2012
Notes: This exam has 10 questions. The duration is 3 hours. Books, notes, and
calculators are allowed, but not computers, cellphones or on-line connectivity.
FE2012: Question 1.
A multiplicity of choices
a) In listing a property, real esta

Chapter 2: Data
Terminology:
Variable a characteristic recorded about an individual
Data specific values of a variable
Observations another word for data
Data table an arrangement of data in rows and columns; also called a
spreadsheet
Record a row in

The University of British Columbia
Sauder School of Business
COMMERCE 291
Midterm Exam, October 22, 2014, 2:30 3:50 pm
Name: _ Student Number: _
(Underline your family name)
Instructions Please read them ALL before turning the page!
Write your name and s

EDMONTON OILERS - 2010-11 Statistics
Uniform # Player Name
14
Jordan Eberle
89
Sam Gagner
4
Taylor Hall
83
Ales Hemsky
27
Dustin Penner
13
Andrew Cogliano
91
Magnus Paajarvi
10
Shawn Horcoff
23
Linus Omark
6
Ryan Whitney
77
Tom Gilbert
28
Ryan Jones
26
Ku

The Normal Model
The data version of the 68-95-99.7 Rule is called The Empirical Rule.
For a symmetric, bell-shaped (i.e. normal) distribution:
68% of the data values are within ! s
95% of the data values are within ! 2s
99.7% of the area values are wi

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 1 and 2
Introduction
The word statistics comes from the Latin word for the state, becau

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 3 and 4
Chapter 3: Surveys and Sampling
Three Principles of Sampling:
1. Examine part o

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 5 and 6
Chapter 5: Displaying and Describing Quantitative Data CONTINUED
Time Series Pl

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 7 and 8
Chapter 6. Correlation and Linear Regression CONTINUED
Remember the formula for

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 9 and 10
Chapter 7. Randomness and Probability
We only need two concepts from Chapter 7

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 5 and 6
Chapter 5: Displaying and Describing Quantitative Data CONTINUED
Time Series Pl

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 13 and 14
Why do we need to know about sampling distributions?
In Chapter 3 we defined

COMMERCE 291 Lecture Notes 2015 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 11 and 12
The Normal Model
The Normal Model or Normal Distribution is by far the most w

Chapter 12: Comparing Two Groups
A. Comparison of Two Means
We are interested in estimating 1 2:
SD(! ! ) =
SE(! ! ) =
!
!
!
!
!
!
!
+ !
!
+
!
!
!
The two versions of the two-sample t-test and confidence interval:
Ho: 1 2 = 0 This can also be written as:

Introduction to Statistical Models
Dependent variable
Y
The objectives of model-building include:
Describe a set of data as simply as possible but without omitting any important
features of the data
Compare several different sets of data
Confirm or ref

Chapter 5
Key Ideas
Random Variables Discrete and Continuous, Expected Value
Probability Distributions Properties, Mean, Variance and Standard Deviation
Unusual Results and the Rare Event Rule
Binomial Distribution Properties, Finding Probabilities
Sectio

Chapter 6
Key Ideas
Density Curve Uniform Distribution, Standard Normal Distribution, Z-Score, Z-table (finding areas above and below values using
them), Sampling Distributions (of the mean, of a proportion), The Central Limit Theorem
Section 6-1: Overvie

Chapter Study Guide
Chapter 6
Correlation and Linear Regression
I
Variance, Covariance and Correlation Coefficient
Sample Variance of One Single Variable (Y):
(
)
s2 =
(mean squares = total sum of squares / (n-1), is average, n = number of
observations.
(

Correlation vs. Regression
! A scatter plot can be used to show the relationship
between two variables
! Correlation analysis is used to measure the strength of
the association (linear relationship) between two
variables
" Correlation is only concerned wi

Chapter 2: Data
Terminology:
Variable a characteristic recorded about an individual
Data specific values of a variable
Observations another word for data
Data table an arrangement of data in rows and columns; also called a
spreadsheet
Record a row in

Chapter 3: Surveys and Sampling
Three Principles of Sampling:
1. Examine part of the whole
Sampling means take a subset (i.e. a sample) of a larger whole population and use the
information about the sample to give information about the population.
A sampl

Chapter 6. Correlation and Linear Regression CONTINUED
Some warnings about the use and abuse of correlation:
1. Beware of the effect of outside (lurking) variables
2. Beware of extrapolation extending the results beyond where you have data
3. Beware of co

Time Series Plots
The values are plotted in time order, with time on the horizontal axis. Time series plots
show change over time as upward or downward trends. They can also show variability
with change in size of fluctuations over time.
Numerical Summari

Example
A survey of U.S. restaurant employees found that 75% said work stress had a negative
impact on their personal lives. A sample of 100 employees of a restaurant chain finds
that 68 answer Yes when asked, Does work stress have a negative impact on yo