This document discusses different types of data and levels of measurement in statistics. It begins by defining qualitative and quantitative data, and the four levels of measurement: nominal, ordinal, interval, and ratio. Examples are provided to demonstrate how to classify different data sets by type and level of measurement. The key differences between the four levels are outlined, including whether the data can be categorized, ordered, have differences calculated, or ratios determined. The document aims to explain the classification of data, which is fundamental to statistical analysis.

1. Slide 1
Elementary Statistics
Seventh Edition
Chapter 1
Introduction to
Statistics
Copyright 2019, 2015, 2012, Pearson Education, Inc.

2. Slide 2Copyright 2019, 2015, 2012, Pearson Education, Inc.
Chapter Outline
• 1.1 An Overview of Statistics
• 1.2 Data Classification
• 1.3 Data Collection and Experimental Design

3. Copyright 2019, 2015, 2012, Pearson Education, Inc. Slide 3
Section 1.2
Data Classification

4. Slide 4Copyright 2019, 2015, 2012, Pearson Education, Inc.
Section 1.2 Objectives
• How to distinguish between qualitative data and
quantitative data
• How to classify data with respect to the four levels
of measurement: nominal, ordinal, interval, and
ratio

5. Slide 5Copyright 2019, 2015, 2012, Pearson Education, Inc.
Types of Data (1 of 2)
Qualitative Data
Consists of attributes, labels, or nonnumerical entries.
Major Place of birth Eye color

6. Slide 6Copyright 2019, 2015, 2012, Pearson Education, Inc.
Types of Data (2 of 2)
Quantitative data
Numerical measurements or counts.
Age Weight of a letter Temperature

7. Slide 7Copyright 2019, 2015, 2012, Pearson Education, Inc.
Example: Classifying Data by Type
The table shows sports-related head injuries treated
in U.S. emergency rooms during a recent five-year
span for several sports.
Which data are qualitative
data and which are
quantitative data?
(Source: BMC Emergency
Medicine)
Sports-Related Head Injuries
Treated in U.S. Emergency Rooms
Sport Head injuries treated
Basketball 131,930
Baseball 83,522
Football 220,258
Gymnastics 33,265
Hockey 41,450
Soccer 98,710
Softball 41,216
Swimming 44,815
Volleyball 13,848

8. Slide 8Copyright 2019, 2015, 2012, Pearson Education, Inc.
Solution: Classifying Data by Type
Sports-Related Head Injuries
Treated in U.S. Emergency Rooms
Sport Head injuries treated
Basketball 131,930
Baseball 83,522
Football 220,258
Gymnastics 33,265
Hockey 41,450
Soccer 98,710
Softball 41,216
Swimming 44,815
Volleyball 13,848
Qualitative Data (Types
of sports are
nonnumerical entries.)
Quantitative Data
(Head injuries treated
are numerical entries.)

9. Slide 9Copyright 2019, 2015, 2012, Pearson Education, Inc.
Levels of Measurement (1 of 3)
Nominal level of measurement
• Qualitative data only
• Categorized using names, labels, or qualities
• No mathematical computations can be made
Ordinal level of measurement
• Qualitative or quantitative data
• Data can be arranged in order, or ranked
• Differences between data entries is not meaningful

10. Slide 10Copyright 2019, 2015, 2012, Pearson Education, Inc.
Example: Classifying Data by Level
(1 of 2)
For each data set, determine whether the data are at the
nominal level or at the ordinal level. Explain your
reasoning. (Source: U.S. Bureau of Labor Statistics)
1. Top five U.S. occupations with the
most job growth (projected 2024)
1. Personal care aides
2. Registered nurses
3. Home health aides
4. Combined food preparation and
serving workers, including fast food
5. Retail salespersons
2. Movie genres
Action
Adventure
Comedy
Drama
Horror

11. Slide 11Copyright 2019, 2015, 2012, Pearson Education, Inc.
Solution: Classifying Data by Level
(1 of 2)
1. Top five U.S. occupations with the
most job growth (projected 2024)
1. Personal care aides
2. Registered nurses
3. Home health aides
4. Combined food preparation and
serving workers, including fast food
5. Retail salespersons
Ordinal level (lists the rank of
five largest job growth
occupations. Data can be
ordered. Difference between
ranks is not meaningful.)
2. Movie genres
Action
Adventure
Comedy
Drama
Horror
Nominal level (lists movie
genres). No mathematical
computations can be made
and cannot be ranked.

12. Slide 12Copyright 2019, 2015, 2012, Pearson Education, Inc.
Levels of Measurement (2 of 3)
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”)

13. Slide 13Copyright 2019, 2015, 2012, Pearson Education, Inc.
Levels of Measurement (3 of 3)
Ratio level of measurement
• Similar to interval level
• Zero entry is an inherent zero (implies “none”)
• A ratio of two data values can be formed
• One data value can be expressed as a multiple of
another

14. Slide 14Copyright 2019, 2015, 2012, Pearson Education, Inc.
Example: Classifying Data by Level
(2 of 3)
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)

15. Slide 15Copyright 2019, 2015, 2012, Pearson Education, Inc.
Example: Classifying Data by Level
(3 of 3)
New York Yankees’
World Series victories (years)
1923, 1927, 1928, 1932, 1936,
1937, 1938, 1939, 1941, 1943,
1947, 1949, 1950, 1951, 1952,
1953, 1956, 1958, 1961, 1962,
1977, 1978, 1996, 1998, 1999,
2000, 2009
2016 American League
home run totals (by team)
Baltimore 253
Boston 208
Chicago 168
Cleveland 185
Detroit 211
Houston 198
Kansas City 147
Los Angeles 156
Minnesota 200
New York 183
Oakland 169
Seattle 223
Tampa Bay 216
Texas 215
Toronto 221

16. Slide 16Copyright 2019, 2015, 2012, Pearson Education, Inc.
Solution: Classifying Data by Level
(2 of 3)
New York Yankees’
World Series victories (years)
1923, 1927, 1928, 1932, 1936,
1937, 1938, 1939, 1941, 1943,
1947, 1949, 1950, 1951, 1952,
1953, 1956, 1958, 1961, 1962,
1977, 1978, 1996, 1998, 1999,
2000, 2009
Interval level (Quantitative
data. Can find a difference
between two dates, but a
ratio does not make sense.)

17. Slide 17Copyright 2019, 2015, 2012, Pearson Education, Inc.
Solution: Classifying Data by Level
(3 of 3) 2016 American League
home run totals (by team)
Baltimore 253
Boston 208
Chicago 168
Cleveland 185
Detroit 211
Houston 198
Kansas City 147
Los Angeles 156
Minnesota 200
New York 183
Oakland 169
Seattle 223
Tampa Bay 216
Texas 215
Toronto 221
Ratio level (Can find differences and write ratios.)

18. Slide 18Copyright 2019, 2015, 2012, Pearson Education, Inc.
Summary of Four Levels of
Measurement (1 of 3)
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

19. Slide 19Copyright 2019, 2015, 2012, Pearson Education, Inc.
Summary of Four Levels of
Measurement (2 of 3)
blank cell Example of a data set Meaningful calculations
Nominal
level
(Qualitative
data)
Types of Shows Televised by a Network
Comedy Documentaries
Drama Cooking
Reality Shows Soap Operas
Sports Talk Shows
Put in a category.
For instance, a show
televised by the network
could be put into one of the
eight categories shown.
Ordinal level
(Qualitative or
quantitative
data)
Motion Picture Association of America Ratings
Description
G General Audiences
PG Parental Guidance Suggested
PG-13 Parents Strongly Cautioned
R Restricted
NC-17 No One 17 and Under Admitted
Put in a category and put in
order.
For instance, a PG rating
has a stronger restriction
than a G rating.

20. Slide 20Copyright 2019, 2015, 2012, Pearson Education, Inc.
Summary of Four Levels of
Measurement (3 of 3)