Business Analytics
Business Analytics
3rd Edition
ISBN: 9780135231715
Author: Evans
Publisher: PEARSON
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Chapter 4, Problem 1PE
To determine

To find: the type of data does each of the survey items represent.

Expert Solution & Answer
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Answer to Problem 1PE

Gender data is categorical data

Age data is ratio data

Ethnicity data is categorical data

Length of residency data is ratio data

Overall satisfaction with city services data is ordinal

Quality of school’s data is ordinal

Explanation of Solution

Given:

Gender

Age

Ethnicity

Overall satisfaction with city services

Quality of schools

Gender data is categorical data because gender consists of male and female, which are two types of genders based on characteristics and do not have any meaningful numerical value.

Gender data is not ordinal data because they cannot be sorted based on any ranking. Gender data is not interval or ratio data because it's not numerical.

Age data is ratio data because a person's age is a numerical value. The age zero years is a natural and meaningful zero.

Age data are not categorical data because age cannot be categorized based on characteristics. Age data is not ordinal data because ages have meaningful numerical values. Age data is not interval data because ages have a natural zero.

Ethnicity data is categorical data because ethnic classes are categories based on characteristics.

Ethnicity data is not ordinal data because they cannot be ranked in any meaningful way. Ethnicity data is not interval or ratio data because it is not numeric.

Length of residency data is ratio data because the length refers to length of time, typically measured in numbers of years. The length of time zero years is a natural zero.

Length of residency data is not categorical data since lengths of time is not categories based on characteristics. It is not ordinal data because lengths of time have meaningful numerical values. It is not interval data because lengths of time have a natural zero.

Overall satisfaction with city services data is rated using a scale of 1 to 5, representing the ratings poor to excellent. This data will be ordinal since there is an order from poor to excellent, and there is a meaningful comparison between the data values.

The data is not categorical since the ratings - poor to excellent are not merely categories based on characteristics, but are rankings. It is not interval or ratio data because the numerical values 1 to 5 do not hold any meaning quantitatively.

Quality of school’s data is rated using a scale of 1 to 5, representing the ratings poor to excellent. The data are ordinal since there is an order from poor to excellent, and there is a meaningful comparison between the data values.

The data is not categorical since the ratings poor to excellent are not merely categories based on characteristics, but are rankings. It is not interval or ratio data because the numerical values 1 to 5 do not hold any meaning quantitatively.

Conclusion:

Therefore,

Gender data is categorical data

Age data is ratio data

Ethnicity data is categorical data

Length of residency data is ratio data

Overall satisfaction with city services data is ordinal

Quality of school’s data is ordinal

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Chapter 4 Solutions

Business Analytics

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