MAS Ch. 1 (1-60)

In observational studies, the variable of interest a. is not controlled. b. is controlled. c. must be numerical. d. cannot be numerical.

a. is not controlled.

The subject of data mining deals with a. methods for developing useful decision-making information from large data bases. b. keeping data secure so that unauthorized individuals cannot access the data. c. computational procedure for data analysis. d. computing the average for data.

a. methods for developing useful decision-making information from large data bases.

Some hotels ask their guests to rate the hotel's services as excellent, very good, good, and poor. This is an example of the a. ordinal scale. b. ratio scale. c. nominal scale. d. interval scale.

a. ordinal scale.

Income is an example of a variable that uses the a. ratio scale. b. interval scale. c. nominal scale. d. ordinal scale.

a. ratio scale.

The scale of measurement that has an inherent zero value defined is the a. ratio scale. b. nominal scale. c. ordinal scale. d. interval scale.

a. ratio scale.

The collection of all elements of interest in a particular study is a. the population. b. the sample. c. statistical inference. d. descriptive statistics.

a. the population.

Data collected over several time periods are a. time series data. b. time controlled data. c. cross-sectional data. d. categorical data.

a. time series data.

In a questionnaire, respondents are asked to mark their gender as male or female. The scale of measurement for gender is a. ordinal scale. b. nominal scale. c. ratio scale. d. interval scale.

b. nominal scale.

The scale of measurement used for variable data that is simply a label for the purpose of identifying the attribute of an element is the a. ratio scale. b. nominal scale. c. ordinal scale. d. interval scale.

b. nominal scale.

The number of observations will always be the same as the a. number of variables. b. number of elements. c. population size. d. sample size.

b. number of elements.

In a data set, the number of elements will always be the same as the number of a. independent variables. b. observations. c. data points. d. dependent variables.

b. observations.

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

b. observations.

Ordinary arithmetic operations are meaningful a. only with categorical data. b. only with quantitative data. c. either with quantitative or categorical data. d. with neither quantitative or categorical data.

b. only with quantitative data

The scale of measurement that is used to rank order the observation for a variable is called the a. ratio scale. b. ordinal scale. c. nominal scale. d. interval scale.

b. ordinal scale.

How many scales of measurement exist? a. 2 b. 4 c. 6 d. 8

b. 4

Statistical studies in which researchers control variables of interest are a. experimental studies. b. control observational studies. c. non-experimental studies. d. observational studies.

a. experimental studies.

Which scale of measurement can be either numeric or non-numeric? a. Nominal b. Ratio c. Interval d. Quantitative

a. Nominal

Which of the following is a scale of measurement? a. Ratio b. Primal c. Divisional d. Remedial

a. Ratio

Arithmetic operations are inappropriate for a. categorical data. b. quantitative data. c. both categorical and quantitative data. d. large data sets.

a. categorical data.

In a post office, the mailboxes are numbered from 1 to 4,500. These numbers represent a. categorical data. b. quantitative data. c. either categorical or quantitative data. d. since the numbers are sequential, the data is quantitative.

a. categorical data.

In a questionnaire, respondents are asked to mark their gender as male or female. Gender is an example of a(n) a. categorical variable. b. quantitative variable. c. interval-scale variable. d. ordinal-scale variable.​

a. categorical variable.

For ease of data entry into a university database, 1 denotes that the student is an undergraduate and 2 indicates that the student is a graduate student. In this case data are a. categorical. b. quantitative. c. either categorical or quantitative. d. neither categorical nor quantitative.

a. categorical.

The entities on which data are collected are a. elements. b. populations. c. samples. d. observations.

a. elements.

An interviewer has made an error in recording the data. This type of error is known as a. an experimental error. b. a data acquisition error. c. a non-experimental error. d. a conglomerate error.

b. a data acquisition error.

Temperature is an example of a. a categorical variable. b. a quantitative variable. c. either a quantitative or categorical variable. d. neither a quantitative nor categorical variable.

b. a quantitative variable.

Data measured a nominal scale a. must be alphabetic. b. can be either numeric or nonnumeric. c. must be numeric. d. must rank order the data.

b. can be either numeric or nonnumeric.

The owner of a factory regularly requests a graphical summary of all employees' salaries. The graphical summary of salaries is an example of a. a sample. b. descriptive statistics. c. statistical inference. d. an experiment.

b. descriptive statistics.

The summaries of data, which may be tabular, graphical, or numerical, are referred to as a. inferential statistics. b. descriptive statistics. c. statistical inference. d. data analytics.

b. descriptive statistics.

. In experimental studies, the variable of interest a. is not controlled. b. is controlled. c. must be numerical. d. cannot be numerical.

b. is controlled.

The measurement scale suitable for quantitative data is a. ordinal scale. b. nominal scale. c. either interval or ratio scale. d. only interval scale.

c. either interval or ratio scale.

Five hundred residents of a city are polled to obtain information on voting intentions in an upcoming city election. The five hundred residents in this study is an example of a(n) a. census. b. sample. c. observation. d. population.

b. sample

Temperature is an example of a variable that uses a. the ratio scale. b. the interval scale. c. the ordinal scale. d. either the ratio or the ordinal scale.

b. the interval scale.

The Department of Transportation of a city has noted that on the average there are 17 accidents per day. The average number of accidents is an example of​ a. ​descriptive statistics. b. ​statistical inference. c. ​a sample. d. ​a population.

b. ​statistical inference.

Quantitative data a. are always non-numeric. b. may be either numeric or non-numeric. c. are always numeric. d. are never numeric.

c. are always numeric.

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

c. are labels used to identify attributes of elements.

Arithmetic operations provide meaningful results for variables that a. use any scale of measurement except nominal. b. appear as non-numerical values. c. are quantitative. d. have non-negative values.

c. are quantitative

Data a. are always numeric. b. are always non-numeric. c. are the raw material of statistics. d. are always categorical.

c. are the raw material of statistics.

Data collected at the same, or approximately the same point in time are a. time series data. b. approximate time series data. c. cross-sectional data. d. approximate data.

c. cross-sectional data.

The process of analyzing sample data in order to draw conclusions about the characteristics of a population is called a. descriptive statistics. b. statistical inference. c. data analysis. d. data summarization.

c. data analysis.

All the data collected in a particular study are referred to as the a. inference. b. variable. c. data set. d. population.

c. data set.

The process of capturing, storing, and maintaining data is known as a. data manipulation. b. data mining. c. data warehousing. d. big data.

c. data warehousing.

Statistical inference a. refers to the process of drawing inferences about the sample based on the characteristics of the population. b. is the same as descriptive statistics. c. is the process of drawing inferences about the population based on the information taken from the sample. d. is the same as a census.

c. is the process of drawing inferences about the population based on the information taken from the sample.

The data measured on ordinal scale exhibits all the properties of data measured on a. ratio scale. b. interval scale. c. nominal scale. d. nominal and interval scales.

c. nominal scale.

In a sample of 400 students in a university, 80 or 20% are Business majors. Based on the above information, the school's paper reported that "20% of all the students at the university are Business majors." This report is an example of a. a sample. b. a population. c. statistical inference. d. descriptive statistics.

c. statistical inference.

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

c. variable.

Which of the following variables use the ratio scale of measurement? a. Social security number b. Temperature c. Gender d. Income

d. Income

Which of the following is not a scale of measurement? a. Nominal b. Ordinal c. Interval d. Primal

d. Primal

Social security numbers consist of numeric values. Therefore, social security number is an example of a. a quantitative variable. b. either a quantitative or a categorical variable. c. an exchange variable. d. a categorical variable.

d. a categorical variable.

A portion of the population selected to represent the population is called a. statistical inference. b. descriptive statistics. c. a census. d. a sample.

d. a sample.

Census refers to a. an experimental study to collect data on the entire population. b. an experimental study to collect data on a sample. c. a survey to collect data on a sample. d. a survey to collect data on the entire population.

d. a survey to collect data on the entire population.

In a sample of 800 students in a university, 240 or 30% are Business majors. The 30% is an example of a. a sample. b. a population. c. statistical inference. d. descriptive statistics.

d. descriptive statistics.

The average age in a sample of 190 students at City College is 22. As a result of this sample, it can be concluded that the average age of all the students at City College a. must be more than 22, since the population is always larger than the sample. b. must be less than 22, since the sample is only a part of the population. c. could not be 22. d. is around 22.

d. is around 22.

Categorical data a. must be numeric. b. must be nonnumeric. c. cannot be numeric. d. may be either numeric or nonnumeric.

d. may be either numeric or nonnumeric.

Statistical studies in which researchers do not control variables of interest are a. experimental studies. b. uncontrolled experimental studies. c. not of any value. d. observational studies.

d. observational studies.

Income is an example of a. categorical data. b. either categorical or quantitative data. c. nominal data. d. quantitative data.

d. quantitative data.

The height of a building, measured in feet, is an example of a. categorical data. b. either categorical or quantitative data. c. feet data. d. quantitative data.

d. quantitative data.

The weight of a candy bar in ounces is an example of a. categorical data. b. either categorical or quantitative data. c. weight data. d. quantitative data.

d. quantitative data.

A statistics professor asked students in a class their ages. On the basis of this information, the professor states that the average age of all the students in the university is 24 years. This is an example of a. a census. b. descriptive statistics. c. an experiment. d. statistical inference.

d. statistical inference.

Since a sample is a subset of the population, the sample mean a. is always smaller than the mean of the population. b. is always larger than the mean of the population. c. must be equal to the mean of the population. d. varies around the mean of the population.

d. varies around the mean of the population.

Different methods of developing useful information from large data bases are dealt with under a. data manipulation. b. data warehousing. c. big data. d. data mining.

d. data mining.