Instructor Resource Guide
Business Statistics
Fourth Canadian Edition
Norean R. Sharpe
St. John’s University
Richard D. De Veaux
Williams College
Paul F. Velleman
Cornell University
David Wright
University of Ottawa
, Contents
About This Guide 0-1
Part I: Exploring and Collecting Data
Chapter 1 An Introduction to Statistics 1-1
Chapter 2 Data 2-1
Chapter 3 Surveys and Sampling 3-1
Chapter 4 Displaying and Describing Categorical Data 4-1
Chapter 5 Displaying and Describing Quantitative Data 5-1
Chapter 6 Scatterplots, Association, and Correlation 6-1
Chapter 7 Introduction to Linear Regression 7-1
Part II: Understanding Probability Distributions and Statistical Inference
Chapter 8 Randomness and Probability 8-1
Chapter 9 Random Variables and Probability Distributions 9-1
Chapter 10 Sampling Distributions 10-1
Chapter 11 Confidence Intervals for Proportions 11-1
Chapter 12 Testing Hypotheses About Proportions 12-1
Chapter 13 Confidence Intervals and Hypothesis Tests for Means 13-1
Chapter 14 Comparing Two Means 14-1
Chapter 15 Design of Experiments and Analysis of Variance, ANOVA 15-1
Chapter 16 Interference for Counts: Chi-Square Tests 16-1
Chapter 17 Nonparametric Methods 17-1
Part III: Exploring Relationships Among Variables
Chapter 18 Inference for Regression 18-1
Chapter 19 Understanding Regression Residuals 19-1
Chapter 20 Multiple Regression 20-1
Chapter 21 Building Multiple Regression Models 21-1
Part IV: Using Statistics for Decision Making
Chapter 22 Time Series Analysis 22-1
Chapter 23 Decision Making and Risk 23-1
Chapter 24 Quality Control 24-1
, Chapter 1
An Introduction to Statistics
What’s It About?
This chapter is about Statistics – what it is and why we care. It also describes the important
features of the text.
Comments
Do expect your students to read the book. Give them specific reading assignments, starting with
this first chapter. We’ve tried to make the book engaging. You can assign a few pages of reading
along with some problems each night. Chapter 1 makes a good opening assignment.
This is the students’ first look at the style of the book, and we do lay it on more heavily here than
we will when discussing, say, confidence intervals. We want to shake things up. We want them to
notice that this is not the same old math or science textbook they’ve seen before. And we’d like to
get them on our side. That’s the reason for the humour and self-deprecating remarks.
Every Statistics text starts with a definition of Statistics. We do too, but ours is different. And the
difference matters. We say that Statistics is a way of reasoning and that the goal is to help us
understand the world. We’ve found it helpful to reinforce this idea throughout the book, especially
when we get into the methods sections of the course. This book is first and primarily about
statistical thinking. Methods, definitions, and skills are all here, but each is presented with the
purpose of understanding the world so we can make better business decisions. That’s why every
guided example follows the Plan, Do, Report pattern, starting with careful reasoning and
concluding with a sentence or two telling what we’ve learned about the world.
It is easy to be drawn into a focus on definitions, on algorithms, and on getting the “right answer.”
Those are easier to teach and certainly easier to grade. Please resist the temptation. If you can help
your students to stay focused on statistical thinking and understanding, this course can change the
way they view the world.
We have included a section on “20th and 21st Century Statistics” that describes how statistics has
evolved, particularly today with its uses in analytics.
Since this text is designed for business students, we have also included a section on how the
various business disciplines use statistics. This may help to address the commonly heard question
of “why do I need to know this?”
A Note on Teaching
We don’t spend an entire class period on this chapter; in fact, sometimes we just start right in on
Chapter 2. Chapter 1 is meant to be read by students not to them. Discuss the important definitions,
collect some data, and move on as fast as you can. We’ve got a lot to cover and can’t afford a full
class just to get moving.
Looking Ahead
Most of our own students actually do the reading. (Yes, we were surprised at first.) If you can
hook students on reading the text, there are big benefits later on. As they read they learn that the
, book is a valuable resource to help them understand sticky concepts, to help lead them through
writing complete and clear solutions, and to help them avoid common mistakes.
Class Do’s
One of our favourite definitions says “Statistics is the art of distilling meaning from data.” Data
have a story to tell. Our objective is to uncover that story. Be sure to distinguish the differences
between data and statistics. Collect some data in class, and ask students to look for interesting facts
hiding there. Or have students gather current economic or business data from the internet.
Encourage students to think about the concepts and definitions in this chapter. For example, why
do we talk about “a statistic” when we don’t discuss “a mathematic” or “a physic”? Statistics is a
whole that is made up of many parts, and each of those parts has its own meaning and its own
story to tell. Ask students about how different companies may utilise large amounts of data. For
example, what data might a large company such as The Bay or Fairmont Hotels & Resorts look at
and for what purpose?
The Importance of What You Don’t Say
One of the reasons Statistics can be difficult to teach is that we often deal with vague concepts.
Students and instructors both like clear definitions; they’re easier to teach, learn, and grade. But
reasonable people can disagree about whether a histogram is symmetric or skewed, whether a
straggling point is really an outlier or just the largest value, or whether the spread really is the
same in two groups we want to compare. It is important to allow students their own opinions and
insights into data.
Avoid the temptation to lead students in any particular direction or give them hints about how to
examine the data you collected. They know some things to do—they’ll find percents and averages,
maybe draw some simple graphs, and write a few sentences about what they see. Just let it happen.
You’ll have plenty of chances to suggest, lead, and modify later on.
The motivation of hoping to understand the world is quite sufficient to justify thinking beyond the
numbers at hand. This is not the time to introduce technical concepts of inference. We’d rather not
see these ideas yet (and you won’t find them this early in the text). We all know that we’ll be
heading that way eventually, but if we make reasoning about patterns in the data too formal too
soon, we’ll stifle students’ interest and enthusiasm and burden them with a lot of terms they don’t
have a context for just yet.
Class Examples
Take a quick class survey. Make sure that you have a good mix of quantitative and categorical
variables. Some possible variables are gender, Program of Study (Acct’g, Fn’c, Mrkt’g, etc.)
number of siblings, number of provinces visited, and shoe size. Start passing a survey sheet around
at the very beginning of class; it can circulate quickly while you are introducing yourself and
talking about the course, expectations, and so on. Passing out slips of paper with a list of states for
each student to check off will speed things up, so we provide that, too. After you’ve entered the
data into the computer, give the students the data file and ask them what story it tells about their
class. You’ll find that a lot of important issues will surface during discussions. As new methods
are introduced throughout the course, you can continue using the data for examples.
Hints: Data are rarely as simple as they seem. Suggest the variables above, and then pause for
some discussion. Does touching down at an airport qualify as “visiting” a province? Does an only
Business Statistics
Fourth Canadian Edition
Norean R. Sharpe
St. John’s University
Richard D. De Veaux
Williams College
Paul F. Velleman
Cornell University
David Wright
University of Ottawa
, Contents
About This Guide 0-1
Part I: Exploring and Collecting Data
Chapter 1 An Introduction to Statistics 1-1
Chapter 2 Data 2-1
Chapter 3 Surveys and Sampling 3-1
Chapter 4 Displaying and Describing Categorical Data 4-1
Chapter 5 Displaying and Describing Quantitative Data 5-1
Chapter 6 Scatterplots, Association, and Correlation 6-1
Chapter 7 Introduction to Linear Regression 7-1
Part II: Understanding Probability Distributions and Statistical Inference
Chapter 8 Randomness and Probability 8-1
Chapter 9 Random Variables and Probability Distributions 9-1
Chapter 10 Sampling Distributions 10-1
Chapter 11 Confidence Intervals for Proportions 11-1
Chapter 12 Testing Hypotheses About Proportions 12-1
Chapter 13 Confidence Intervals and Hypothesis Tests for Means 13-1
Chapter 14 Comparing Two Means 14-1
Chapter 15 Design of Experiments and Analysis of Variance, ANOVA 15-1
Chapter 16 Interference for Counts: Chi-Square Tests 16-1
Chapter 17 Nonparametric Methods 17-1
Part III: Exploring Relationships Among Variables
Chapter 18 Inference for Regression 18-1
Chapter 19 Understanding Regression Residuals 19-1
Chapter 20 Multiple Regression 20-1
Chapter 21 Building Multiple Regression Models 21-1
Part IV: Using Statistics for Decision Making
Chapter 22 Time Series Analysis 22-1
Chapter 23 Decision Making and Risk 23-1
Chapter 24 Quality Control 24-1
, Chapter 1
An Introduction to Statistics
What’s It About?
This chapter is about Statistics – what it is and why we care. It also describes the important
features of the text.
Comments
Do expect your students to read the book. Give them specific reading assignments, starting with
this first chapter. We’ve tried to make the book engaging. You can assign a few pages of reading
along with some problems each night. Chapter 1 makes a good opening assignment.
This is the students’ first look at the style of the book, and we do lay it on more heavily here than
we will when discussing, say, confidence intervals. We want to shake things up. We want them to
notice that this is not the same old math or science textbook they’ve seen before. And we’d like to
get them on our side. That’s the reason for the humour and self-deprecating remarks.
Every Statistics text starts with a definition of Statistics. We do too, but ours is different. And the
difference matters. We say that Statistics is a way of reasoning and that the goal is to help us
understand the world. We’ve found it helpful to reinforce this idea throughout the book, especially
when we get into the methods sections of the course. This book is first and primarily about
statistical thinking. Methods, definitions, and skills are all here, but each is presented with the
purpose of understanding the world so we can make better business decisions. That’s why every
guided example follows the Plan, Do, Report pattern, starting with careful reasoning and
concluding with a sentence or two telling what we’ve learned about the world.
It is easy to be drawn into a focus on definitions, on algorithms, and on getting the “right answer.”
Those are easier to teach and certainly easier to grade. Please resist the temptation. If you can help
your students to stay focused on statistical thinking and understanding, this course can change the
way they view the world.
We have included a section on “20th and 21st Century Statistics” that describes how statistics has
evolved, particularly today with its uses in analytics.
Since this text is designed for business students, we have also included a section on how the
various business disciplines use statistics. This may help to address the commonly heard question
of “why do I need to know this?”
A Note on Teaching
We don’t spend an entire class period on this chapter; in fact, sometimes we just start right in on
Chapter 2. Chapter 1 is meant to be read by students not to them. Discuss the important definitions,
collect some data, and move on as fast as you can. We’ve got a lot to cover and can’t afford a full
class just to get moving.
Looking Ahead
Most of our own students actually do the reading. (Yes, we were surprised at first.) If you can
hook students on reading the text, there are big benefits later on. As they read they learn that the
, book is a valuable resource to help them understand sticky concepts, to help lead them through
writing complete and clear solutions, and to help them avoid common mistakes.
Class Do’s
One of our favourite definitions says “Statistics is the art of distilling meaning from data.” Data
have a story to tell. Our objective is to uncover that story. Be sure to distinguish the differences
between data and statistics. Collect some data in class, and ask students to look for interesting facts
hiding there. Or have students gather current economic or business data from the internet.
Encourage students to think about the concepts and definitions in this chapter. For example, why
do we talk about “a statistic” when we don’t discuss “a mathematic” or “a physic”? Statistics is a
whole that is made up of many parts, and each of those parts has its own meaning and its own
story to tell. Ask students about how different companies may utilise large amounts of data. For
example, what data might a large company such as The Bay or Fairmont Hotels & Resorts look at
and for what purpose?
The Importance of What You Don’t Say
One of the reasons Statistics can be difficult to teach is that we often deal with vague concepts.
Students and instructors both like clear definitions; they’re easier to teach, learn, and grade. But
reasonable people can disagree about whether a histogram is symmetric or skewed, whether a
straggling point is really an outlier or just the largest value, or whether the spread really is the
same in two groups we want to compare. It is important to allow students their own opinions and
insights into data.
Avoid the temptation to lead students in any particular direction or give them hints about how to
examine the data you collected. They know some things to do—they’ll find percents and averages,
maybe draw some simple graphs, and write a few sentences about what they see. Just let it happen.
You’ll have plenty of chances to suggest, lead, and modify later on.
The motivation of hoping to understand the world is quite sufficient to justify thinking beyond the
numbers at hand. This is not the time to introduce technical concepts of inference. We’d rather not
see these ideas yet (and you won’t find them this early in the text). We all know that we’ll be
heading that way eventually, but if we make reasoning about patterns in the data too formal too
soon, we’ll stifle students’ interest and enthusiasm and burden them with a lot of terms they don’t
have a context for just yet.
Class Examples
Take a quick class survey. Make sure that you have a good mix of quantitative and categorical
variables. Some possible variables are gender, Program of Study (Acct’g, Fn’c, Mrkt’g, etc.)
number of siblings, number of provinces visited, and shoe size. Start passing a survey sheet around
at the very beginning of class; it can circulate quickly while you are introducing yourself and
talking about the course, expectations, and so on. Passing out slips of paper with a list of states for
each student to check off will speed things up, so we provide that, too. After you’ve entered the
data into the computer, give the students the data file and ask them what story it tells about their
class. You’ll find that a lot of important issues will surface during discussions. As new methods
are introduced throughout the course, you can continue using the data for examples.
Hints: Data are rarely as simple as they seem. Suggest the variables above, and then pause for
some discussion. Does touching down at an airport qualify as “visiting” a province? Does an only
