1.2 Data Classification

Front 1

Select all the levels of measurement for which data can be qualitative.

A.Ratio

B.Interval

C.Ordinal

D.Nominal

Back 1

Ordinal- (ranking)

Nominal- (Names or labels)

Front 2

Define Qualitative Data

Back 2

It consists of attributes, labels, or non-numerical entries.

Front 3

Define Quantitative Data

Back 3

It consists of numerical measurements or counts.

Front 4

True or False?

Data at the ordinal level are quantitative only.

Back 4

False. Data at the ordinal level can be qualitative or quantitative.

Data at the ordinal level can be qualitative or quantitative. Data at this level can be arranged in​ order, or​ ranked, but differences between data entries are not meaningful.

Front 5

True or False?

More types of calculations can be performed with data at the nominal level than with data at the interval level

Back 5

False. More types of calculations can be performed with data at the interval level than with data at the nominal level.

Data at the nominal level can be put in a category. Data at the interval level can be put in a​ category, put in​ order, and you can find differences between values. ​Therefore, more types of calculations can be performed with data at the interval level than with data at the nominal level.

Front 6

Determine whether the variable is qualitative or quantitative. Explain your reasoning.

Distance in miles from one city to another.

Back 6

The variable is quantitative because distance in miles is found by measuring or counting.

Front 7

Determine whether the variable is qualitative or quantitative. Explain your reasoning.

Medal won in race.

Back 7

The variable is qualitative because medal won in race describes an attribute or characteristic.

Front 8

The years that a particular team won the world series are shown below.

1954 1972 1986 1987 1988 1994 2006 2009 2012

Determine the level of measurement of the data set. Explain your reasoning.

Back 8

Interval. The data can be ordered and differences between data entries are​ meaningful, but a zero entry is not an inherent zero.

Front 9

The jersey numbers for players on a basketball team are listed.

What is the data​ set's level of​ measurement? Explain your reasoning.

Back 9

Nominal. The data are categorized using​ numbers, but no mathematical computations can be made.

Front 10

The times of a day when a person logs on to facebook are shown below.

What is the level of measurement of the data​ set? Explain your reasoning.

Back 10

Interval. The data can be ordered and differences between data entries are​ meaningful, but a zero entry is not an inherent zero.

Front 11

Define Nominal

Back 11

Qualitative.

Categorized using names, labels or qualities.

Front 12

Define Ordinal

Back 12

Qualitative or Quantitative.

Data can be arranged in order, or ranked, but differences between data entries are not meaningful.

Front 13

Define Interval

Back 13

Can be ordered, and meaningful differences between data entries can be calculated. In this level, a zero entry simply represents a position on a scale.

Front 14

Define Ratio

Back 14

similar to data at an interval level with the added property that a zero entry is an inherent zero.

Front 15

What is the level of measurement for ​"Change in health (scale of −5 to 5)​"?

Back 15

Ordinal

Front 16

What is the level of measurement for ​"Marital status​"?

Back 16

Nominal

Front 17

What is the level of measurement for ​"Year of birth​"?

Back 17

Interval

Front 18

What is the level of measurement for ​"Weight​"?

Back 18

Ratio