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Chapter 1


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Description 

Chapter 1
Data and
Decisions




Copyright © 2015 Pearson Education. All rights reserved. 1-1
1.1 What Are Data?

Businesses have always relied on data for planning and to
improve efficiency and quality.

Most modern businesses collect information on virtually every
transaction performed by the organization, including every item
bought or sold.

These data are recorded and stored electronically, in vast digital
repositories called data warehouses.




Copyright © 2015 Pearson Education. All rights reserved. 1-2
1.1 What Are Data?

In the past few decades these data warehouses have grown
enormously in size, and with the use of ever more powerful
computers and software, the information contained in them is
accessibleand used to help make decisions.

The huge capacity of these warehouses has given rise to the
term Big Data to describe data sets so large that traditional
methods of storage and analysis are inadequate.




Copyright © 2015 Pearson Education. All rights reserved. 1-3
1.1 What Are Data?

Data collected for recording the companies’ transactions is
called transactional data.

The process of using transactional data to make other decisions
and predictions, is sometimes called data mining or predictive
analytics.

Business analytics describes any use of statistical analysis to
drive business decisions from data.




Copyright © 2015 Pearson Education. All rights reserved. 1-4
1.1 What Are Data?
All data have a context.

Data values or observations are information collected regarding some
subject. The “Five W’s”: who, what, when, where, and (if possible) why. Often
we add how to the list.

Data can be numbers, names, etc., and tells us the “Who and What”.

Data are often organized into a data table like that below.




Copyright © 2015 Pearson Education. All rights reserved. 1-5
1.1 What Are Data?
The rows of a data table correspond to individual cases about Whom
we record some characteristics.

These characteristics may be collected on or about …

• respondents – individuals who answer a survey

• subjects or participants – people in an experiment

• experimental units – animals, plants, websites, or other inanimate
objects



Cases


Copyright © 2015 Pearson Education. All rights reserved. 1-6
1.1 What Are Data?
The characteristics recorded about each individual or case
are called variables.

These are usually shown as the columns of a data table and
identify What has been measured.


Variables






Copyright © 2015 Pearson Education. All rights reserved. 1-7
1.1 What Are Data?
Metadata typically contains information about how,
when, and where (and possibly why) the data were collected;
who each case represents; and the definitions of all the
variables.

Data are typically saved in a spreadsheet or data table where
the rows represent cases and the columns represent variables.




Copyright © 2015 Pearson Education. All rights reserved. 1-8
1.1 What Are Data?

Data tables are cumbersome for complex data sets, so often
two or more separate data tables are linked together in a
relational database so that information can be merged across
them.

Each data table included in the database is a relation because it
is about a specific set of cases with information about each of
these cases for all the variables.




Copyright © 2015 Pearson Education. All rights reserved. 1-9
1.1 What Are Data?
Example: A typical relational database is provided consisting of three
relations: customer data, item data, and transaction data.



For example, we
can look up a
customer to see
what items they
purchased, or we
may look up an item
to see who
purchased it.



Copyright © 2015 Pearson Education. All rights reserved. 1-10
1.1 What Are Data?
Example: Credit Card Bank
Carly, a marketing manager at a credit card bank, wants to know if an offer mailed
3 months ago has affected customers’ use of their cards. To answer that, she asks the
information technology department to assemble the following information for each
customer:

Total spending on the card during the 3 months before the offer (Pre Spending)
Total spending for 3 months after the offer (Post Spending)
The customer’s Age (by category)
That kind of expenditure they made (Segment)
If customers are enrolled in the website (Enroll?)
What offer they were sent (Offer)
The amount each customer spent on the card in their segment (Segment Spend)

Identify the cases and the variables. Describe as many of the W’s as you can for this
data set.


Copyright © 2015 Pearson Education. All rights reserved. 1-11
1.1 What Are Data?
Example: Credit Card Bank

The cases are individual customers of the credit card bank.

The data are from the internal records of the credit card bank for the past 6
months (3 months before and 3 months after an offer was sent to the
customers).

The variables include the account ID of the customer (Account ID) and the
amount charged on the card before (Pre Spending) and after (Post Spending)
the offer was sent out.

Also included are the customer’s Age, marketing Segment, whether they
enrolled on the website (Enroll?), what offer they were sent (Offer), and how
much they charged on the card in their marketing segment (Segment Spend).


Copyright © 2015 Pearson Education. All rights reserved. 1-12
1.2 Variable Types
When a variable names categories and answers questions
about how cases fall into those categories, it is called a
categorical or qualitative variable.

When a variable has measured numerical values with units and
the variable tells us about the quantity of what is measured, it is
called a quantitative variable.




Copyright © 2015 Pearson Education. All rights reserved. 1-13
1.2 Variable Types
Categorical variables…

• arise from descriptive responses to questions like “What kind of
advertising do you use?”.

• may only have two possible values (like “yes” or “no”).

• may be a number like a zip code.




Copyright © 2015 Pearson Education. All rights reserved. 1-14
1.2 Variable Types
Quantitative variables must have units. The units indicate…

• how each value has been measured.

• the corresponding scale of measurement.

• how much of something we have.

• how far apart two values are.




Copyright © 2015 Pearson Education. All rights reserved. 1-15
1.2 Variable Types
Some variables can be both categorical and quantitative.
How data are classified depends on Why we are collecting the
data.

For example, variable Age is obviously the quantitative value,
measured in years, that may be used for finding the average age
of customers.

But, Age can also be the categorical value, e.g. child, teen, adult,
or senior, used to classify books for an internet store.




Copyright © 2015 Pearson Education. All rights reserved. 1-16
1.2 Variable Types
Identifiers

An identifier variable is a unique identifier assigned to each
individual or item in a group.

For example, social security numbers, student ID numbers,
tracking numbers, transactions numbers, etc. are all identifier
variables for people or items.




Copyright © 2015 Pearson Education. All rights reserved. 1-17
1.2 Variable Types
Identifiers

Identifier variables…

• do not have units.

• are a special kind of categorical variable.

• are useful in combining data from different sources to avoid
duplication.

• are not variables to be analyzed.



Copyright © 2015 Pearson Education. All rights reserved. 1-18
1.2 Variable Types
Other Data Types

Categorical variables used only to name categories (that don’t
have order) are sometimes called nominal variables.

When data values can be ordered, we say that the variable has
ordinal values. For example, employees can be ranked according
to the number of months employed.

Data can either be numerical or categorical, and both nominal
and ordinal data are classified as categorical. Categorical data
can be counted, grouped and sometimes ranked in order of
importance.


Copyright © 2015 Pearson Education. All rights reserved. 1-19
1.2 Variable Types
Cross-Sectional and Time Series Data

Variables that are measured at regular intervals over time are
called a time series. Typical measuring points are months,
quarters, or years.

When several variables are all measured at the same time point,
the data is called cross-sectional data. For example, data on
sales revenue, number of customers, and expenses
for last month at each Starbucks (more than 20,000 locations as
of 2012) at one point in time would be cross-sectional data.




Copyright © 2015 Pearson Education. All rights reserved. 1-20
1.2 Variable Types
Example: Credit Card Bank

Before she can continue with her analysis, Carly must classify each
variable as being quantitative or categorical (or possibly both), and whether
the data are a time series or cross-sectional.

For quantitative variables, what are the units?

For categorical variables, are they nominal or ordinal?


...

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