Indicate the answer choice that best completes the statement or answers the question.

Name: Class: Date:

Ch. 01: Data and Statistics

Powered by Cognero Page 1 Indicate the answer choice that best completes the statement or answers the question.

1.Different methods of developing useful information from large data bases are dealt with under

• data manipulation.
• data warehousing.
• big data.
• data mining.

2.The process of capturing, storing, and maintaining data is known as

• data manipulation.
• data mining.
• data warehousing.
• big data.

3.The subject of data mining deals with

• methods for developing useful decision-making information from large data bases.
• keeping data secure so that unauthorized individuals cannot access the data.
• computational procedure for data analysis.
• computing the average for data.

4.In a questionnaire, respondents are asked to mark their gender as male or female. The scale of measurement for gender is _____ scale.

• ordinal
• nominal
• ratio
• interval

5.The scale of measurement that is used to rank order the observation for a variable is called the _____ scale.

• ratio
• ordinal
• nominal
• interval

6.A restaurant asks their customers to fill out a questionnaire indicating whether their service was excellent, very good, good, or poor. The rating scale used is an example of the _____ scale.

• ordinal
• ratio
• nominal
• interval

7.The data measured on ordinal scale exhibits all the properties of data measured on

• ratio scale.

Essentials of Statistics for Business & Economics, 10e Jeffrey, Cochran, Fry, Ohlmann, Anderson, Sweeney, Williams (Test Bank All Chapters, 100% Original Verified, A+ Grade) 1 / 4

Name:

Class:

Date:

Ch. 01: Data and Statistics

Powered by Cognero Page 2

• interval scale.
• nominal scale.
• nominal and interval scales.

• Measurement of body temperature is an example of a variable that uses
• the ratio scale.
• the interval scale.
• the ordinal scale.
• either the ratio or the ordinal scale.

• Arithmetic operations provide meaningful results for variables that
• use any scale of measurement except nominal and ordinal.
• appear as non-numerical values.
• are quantitative.
• have non-negative values.

• Height is an example of a variable that uses the _____ scale.
• ratio
• interval
• nominal
• ordinal

• Data measured in a nominal scale
• must be alphabetic.
• can be either numeric or nonnumeric.
• must be numeric.
• must rank order the data.

• The scale of measurement that has an inherent zero value defined is the _____ scale.
• ratio
• nominal
• ordinal
• interval

• The measurement scale suitable for quantitative data is _____ scale.

• the ordinal
• the nominal
• either the interval or ratio
• only the interval

• Data are
• always numeric.
• always non-numeric. 2 / 4

Name:

Class:

Date:

Ch. 01: Data and Statistics

Powered by Cognero Page 3

• the raw material of statistics.
• always categorical.

• The entities on which data are collected are
• elements.
• populations.
• samples.
• observations.

• The set of measurements collected for a particular element are called
• variables.
• observations.
• samples.
• populations.

• A characteristic of interest for the elements is called a
• sample.
• data set.
• variable.
• quality.

• All the data collected in a particular study are referred to as the
• sample.
• variable.
• data set.
• population.

• Quantitative data
• are always non-numeric.
• may be either numeric or non-numeric.
• are always numeric.
• are never numeric.

• In a questionnaire, respondents are asked to mark their marital status as single, married, divorced, or widowed. Marital

status is an example of a(n) _____ variable.

• categorical
• quantitative
• interval-scale
• ordinal-scale

• The number of observations will always be the same as the
• number of variables.
• number of elements.
• population size. 3 / 4

Name:

Class:

Date:

Ch. 01: Data and Statistics

Powered by Cognero Page 4

• sample size.

• Categorical data
• must be numeric.
• must be nonnumeric.
• cannot be numeric.
• may be either numeric or nonnumeric.

• Categorical data
• indicate either how much or how many.
• cannot be numeric
• are labels used to identify attributes of elements.
• must be nonnumeric.

• Ordinary arithmetic operations are meaningful
• only with categorical data.
• only with quantitative data.
• either with quantitative or categorical data.
• with neither quantitative nor categorical data.

• A student’s dormitory room number is an example of
• a quantitative variable.
• either a quantitative or a categorical variable.
• an exchange variable.
• a categorical variable.

• Goals scored in a soccer game is an example of
• a categorical variable.
• a quantitative variable.
• either a quantitative or categorical variable.
• neither a quantitative nor categorical variable.

• For ease of data entry into a university database, 1 denotes that the student is a freshman, 2 indicates a sophomore, 3

indicates a junior, and 4 indicates that the student is a senior. In this case, data are

• categorical.
• quantitative.
• either categorical or quantitative.
• neither categorical nor quantitative.

• Arithmetic operations are inappropriate for
• categorical data.
• quantitative data.
• both categorical and quantitative data.
• large data sets.

• / 4