�ݺ�ߣ

UNIT 3
Data Classification
1
Larson/Farber 4th ed.

Types of Data
• Data sets consist of two types of data:
qualitative data and quantitative data

Types of Data
Qualitative Data consists of attributes, labels,
or nonnumerical entries.
Major
3
Place of birth Eye color

Types of Data
Quantitative data consist of numerical
measurements or counts.
Age Weight of a letter Temperature
4

Qualitative Research Quantitative Research
 Qualitative Research is primarily
exploratory research.it is used to gain
an understanding of underlying
reasons, opinions, and motivations.
 It provides insights into the problem or
helps to develop ideas or hypotheses
for potential quantitative research.
 Qualitative Research is also used to
uncover trends in thought and opinions,
and dive deeper into the problem
 Qualitative data collection methods vary
using unstructured or semi-structured
techniques.
 Quantitative Research is used to quantify
the problem by way of generating
numerical data or data that can be
transformed into usable statistics.
 It is used to quantify attitudes, opinions,
behaviors, and other defined variables –
and generalize results from a larger
sample population.
 Quantitative Research uses measurable
data to formulate facts and uncover
patterns in research.
 Quantitative data collection methods are
much more structured than Qualitative
data collection methods.

 Some common methods include
focus groups (group discussions),
individual interviews, and
participation/observations.
 The sample size is typically small,
and respondents are selected to
fulfil a given quota.
 Focuses on exploring ideas and
formulating a theory or hypothesis
 Analyzed by summarizing,
categorizing and interpreting
 Mainly expressed in words
 Requires few respondents
 Open-ended questions
 Key terms: understanding, context,
complexity, subjectivity
 Quantitative data collection
methods include various forms of
surveys – online surveys, mobile
surveys and kiosk surveys, face-to-
face interviews, telephone
interviews, longitudinal studies,
website interceptors, online polls,
and systematic observations.
 Focuses on testing theories and
hypotheses
 Analyzed through math
and statistical analysis
 Mainly expressed in numbers,
graphs and tables
 Requires many respondents
 Closed (multiple choice) questions
 Key terms: testing, measurement,
objectivity, replicability

 Qualitative Research investigates a
small amount of people, by submitting
them physically the product itself,
thus collecting a great number of
behavioral details on a small sample
of users.
 Qualitative research is a type of
empathic, empirical, exploratory,
direct, physical research. It helps
you understand reasons, motivations,
opinions, trends that hide behind the
more quantitative data of quantitative
research.
 Methods include focus groups,
in-depth interviews, and
reviews of documents for types
of themes
 Primarily inductive process used
to formulate theory or
hypotheses
 More subjective: describes a
problem or condition from the
point of view of those
 Quantitative Research investigates a
large number of people by
submitting questionnaires based on
multiple, numeric answers (0 to 10)
and open end (open answers, just a
few in a quantitative questionnaire).
 Surveys, structured interviews
& observations, and reviews of
records or documents for
numeric information
 Primarily deductive process
used to test pre-specified
concepts, constructs, and
hypotheses that make up a
theory
 More objective: provides
observed effects (interpreted
by researchers) of a program
on a problem or condition

 Text-based
 More in-depth information on a few
cases
 Unstructured or semi-structured
response options
 No statistical tests
 Can be valid and reliable: largely
depends on skill and rigor of the
researcher
 Time expenditure lighter on the
planning end and heavier during the
analysis phase
 Less generalizable
 Qualitative research is a method of
inquiry that develops understanding
on human and social sciences, to find
the way people think and feel.
 Holistic
 Subjective
 Exploratory
 Inductive
 Number-based
 Less in-depth but more breadth of
information across a large number of
cases
 Fixed response options
 Statistical tests are used for analysis
 Can be valid and reliable: largely
depends on the measurement device
or instrument used
 Time expenditure heavier on the
planning phase and lighter on the
analysis phase
 More generalizable
 Quantitative research is a research
method that is used to generate
numerical data and hard facts, by
employing statistical, logical and
mathematical technique.
 Particularistic
 Objective
 Conclusive
 Deductive

Purposive
Verbal
Process-oriented
Generated
Words, pictures and
objects
To explore and discover
ideas used in the ongoing
processes.
Non-structured techniques
like In-depth interviews,
group discussions etc.
Develops initial
understanding
Random
Measurable
Result-oriented
Tested
Numerical data
To examine cause and
effect relationship between
variables.
Structured techniques such
as surveys, questionnaires
and observations.
Recommends final course
of action

Example: Classifying Data by Type
The base prices of several vehicles are shown in
the table. Which data are qualitative data and
which are quantitative data? (Source Ford Motor
Company)
1

Solution: Classifying Data by Type
Quantitative Data
(Base prices of
vehicles models are
numerical entries)
1
Qualitative Data
(Names of vehicle
models are
nonnumerical entries)

Levels of Measurement
• The level of measurement is a
characteristic of data and determines
which statistical calculations are
meaningful.
– There are four levels of measurement:
nominal, ordinal, interval, and ratio.

13
Nominal level of measurement
• Qualitative data only
• Categorized using names, labels, or qualities
– When numbers are used at the nominal level, they
represent a label, for example social secruity numbers
• No mathematical computations can be made

14
Ordinal level of measurement
• Qualitative or quantitative data
• Data can be arranged in order
• Differences between data entries is not
meaningful

Example: Classifying Data by Level
Two data sets are shown. Which data set
consists of data at the nominal level? Which
data set consists of data at the ordinal level?
(Source: Nielsen Media Research)
15

Solution: Classifying Data by Level
Ordinal level (lists the
rank of five TV
programs. Data can be
ordered. Difference
between ranks is not
meaningful.)
Nominal level (lists the
call letters of each
network affiliate. Call
letters are names of
network affiliates.)
16

17
Interval level of measurement
• Quantitative data
• Data can ordered
• Differences between data entries is
meaningful
• Zero represents a position on a scale (not
an inherent zero – zero does not imply
“none”)
– Example: Temperature

18
Ratio level of measurement
• Similar to interval level
• Zero entry is an inherent zero (implies
“none”)
– Example: savings account
• A ratio of two data values can be formed
• One data value can be expressed as a
multiple of another

Example: Classifying Data by Level
Two data sets are shown. Which data set consists
of data at the interval level? Which data set
consists of data at the ratio level? (Source: Major
League Baseball)
19

Solution: Classifying Data by Level
Interval level
(Quantitative data.
Can find a difference
between two dates,
but a ratio does not
make sense.)
Ratio level (Can find
differences and write
ratios.)
20

Summary of Four Levels of Measurement
Level of
Measurement
Put data in
categories
Arrange
data in
order
Subtract
data
values
Determine if one
data value is a
multiple of another
Nominal Yes No No No
Ordinal Yes Yes No No
Interval Yes Yes Yes No
Ratio Yes Yes Yes Yes
Meaningful operations at the four levels of measurement:
21

Homework:
• P12 #1 – 20 all

�ݺ�ߣ

uyyu.pptx

More Related Content

uyyu.pptx