Data Classification

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Section 1.2

Section 1.2 Objectives

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Distinguish between qualitative data and quantitative data

Classify data with respect to the four levels of measurement

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Types of Data

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Qualitative Data Consists of attributes, labels, or nonnumerical entries.Can be separated into different categories that aredistinguished by some nonnumeric characteristics

Major Place of birth Eye color

Example: the genders of college graduates

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Types of Data

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Quantitative data Numerical measurements or counts. Numbersrepresenting counts or measurements.

Age Weight of a letter Temperature

Example: the incomes of college graduates 4

Example: Classifying Data by Type

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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)

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Solution: Classifying Data by Type

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Quantitative Data (Base prices of vehicles models are numerical entries)

Qualitative Data (Names of vehicle models are nonnumerical entries)

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Question: Distinguishing Between Qualitative and Quantitative Variables

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Determine whether the following variables are qualitative or quantitative.

(a) Type of wood used to build a kitchen table.

(b) Number of yards Tiger Woods hits his drives.

(c) Number of times your Internet service goes

down in the next 30 days.

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Levels of Measurement

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Nominal level of measurementQualitative data onlyCategorized using names, labels, or qualitiesNo mathematical computations can be madeExample: survey responses yes, no, undecided

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

meaningfulExample: course grades A, B, C, D, or F

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Example: Classifying Data by Level

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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)

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Solution: Classifying Data by Level

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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.)

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Levels of Measurement

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Interval level of measurementQuantitative dataData can orderedDifferences between data entries is meaningfulZero represents a position on a scale (not an

inherent zero – zero does not imply “none”)Example: years 1000, 2000, 1776, and 1492

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Levels of Measurement

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Ratio level of measurementSimilar to interval levelZero 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 anotherExample: prices of college textbooks

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Example: Classifying Data by Level

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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)

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Solution: Classifying Data by Level

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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.)

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Summary of Four Levels of Measurement

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Level ofMeasurement

Put data in

categories

Arrangedata inorder

Subtractdata

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

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Levels of Measurement

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Nominal - categories only Ordinal - categories with some order Interval - differences but no natural

starting point Ratio - differences and a natural starting point

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Section 1.2 Summary

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Distinguished between qualitative data and quantitative data

Classified data with respect to the four levels of measurement

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