BUSINESS STATISTICS PRACTICE TEST
QUESTIONS / 50+ STUDY GUIDE ACTUAL EXAM
QUESTIONS & COMPLETE ANSWERS AND
DEFINITIONS / 2025
Descriptive Statistics - ANS-methods of organizing, summarizing, and presenting data in an informative
way
Examples of Descriptive Statistics - ANS-Census of the population, the weekly earnings of thousands of
computer programmers, individual responses of 2,000 registered voters regarding their choice for
president of the U.S., average rainfall in a year,
Inferential Statistics - ANS-The methods used to estimate a property of a population on the basis of a
sample....(allows you to make predictions ("inferences") from that data collected from a population)
Examples of Inferential Statistics - ANS-Fuel efficiency measured by miles per gallon of an SUVs currently
in use, for the entire world is the IQ of a women the same as IQ of men,
Population - ANS-The entire set of individuals or objects of interest or the measurements obtained from
all individuals or objects of interest
Sample - ANS-A portion, or part, of the population on interest
Data - ANS-Information collected from the population
Qualitative Variable - ANS-When an object or individual is observed and recorded as a nonnumeric
characteristic.
-we usually count the number of observations for each category and determine what percent are in
each category
Examples of qualitative variables - ANS-gender, beverage preference, type of vehicle owned, state of
birth, eye color, brand of PC, Marital status, hair color
Quantitative Variable - ANS-When a variable can be reported numerically
-either discrete or continuous
Examples of quantitative variables - ANS-balance in your checking account, the ages of company
presidents, the life of a car batter (such as 42 months), number of people employed by a company
, Discrete Variables - ANS-Can assume only certain values, and there are "gaps" between the
values..typically counted
Discrete Variable Examples - ANS-Number of bedrooms in a house (1,2,3,4, etc), number of cars arriving
at Exit 25 by Disney in an hour, number of students in each section of a statistics course. (a home can
have 3 or 4 bedrooms but it can not have 3.56 bedrooms), children in a family, strokes on a golf hole, TV
sets owned
Continuous Variable - ANS-Can assume any value within a specific range...result from measuring
Continuous Variable Example - ANS-air pressure in a tire and the weight of a shipment of tomatoes,
number of ounces of raisins in a box of raisin bran cereal, duration of flights from Orlando to San Diego,
GPA of a particular student could be 3.257633 but the usual practice is to round 3 places, Amount of
income tax paid, weight of a student, yearly rainfall in Tampa, FL
Nominal Data - ANS-Represented as labels or names. They have no order. They can only be classified an
counted. We are limited to to counting the number in each category of the variable
Examples of Nominal Data - ANS--Classification of the 6 colors of M&M milk chocolate candies because
classifying by color, not by order
-Variable gender, counting number of students entering a football game with a student ID and report
how many are women and how many are women
-Jersey numbers of football players, make of a car
Ordinal Data - ANS-Based on a relative ranking or rating of items based on a defined attributive or
qualitative variable. Only ranked or counted. An important characteristic of using a relative scale is that
we cannot distinguish the magnitude of difference between "superior" and "good" is the same as
difference between "poor" and "superior"
Examples are Ordinal Data - ANS--Top ten states for a business climate based on an evaluation of over
20 factors, the states are ranked in order from best to worst climate
-"Overall, how do you rate the quality of instruction in this class?" a students response is recorded on a
relative scale of inferior, poor, good, excellent, and superior.
-your rank in class, team standings in the Pac-10
Interval Data - ANS-The interval or the distance between values is meaningful. Based on a scale with a
known unit of measurement.
Interval Data Example - ANS--Fahrenheit scale, suppose high temperatures on 3 consecutive winter days
in Boston are 28, 31, and 20 degrees F, these temps can be easily ranked, buy we can also determine
interval or distance between temps, can between 10 and 15 degrees and 50 and 55 but 0 is just a point
on the scale. it does not represent the absence of heat or cold.(by our own measurement scale it is
cold)we can not make statements similar to 20 degrees F is twice as warm as 10 degrees.
-women's dress sizes, IQ (intelligence scale), SAT scores.
Ratio-Level Data - ANS-"highest level of measurement", based on a scale with a known unit of
measurement and a meaningful interpretation of of zero on the scale
QUESTIONS / 50+ STUDY GUIDE ACTUAL EXAM
QUESTIONS & COMPLETE ANSWERS AND
DEFINITIONS / 2025
Descriptive Statistics - ANS-methods of organizing, summarizing, and presenting data in an informative
way
Examples of Descriptive Statistics - ANS-Census of the population, the weekly earnings of thousands of
computer programmers, individual responses of 2,000 registered voters regarding their choice for
president of the U.S., average rainfall in a year,
Inferential Statistics - ANS-The methods used to estimate a property of a population on the basis of a
sample....(allows you to make predictions ("inferences") from that data collected from a population)
Examples of Inferential Statistics - ANS-Fuel efficiency measured by miles per gallon of an SUVs currently
in use, for the entire world is the IQ of a women the same as IQ of men,
Population - ANS-The entire set of individuals or objects of interest or the measurements obtained from
all individuals or objects of interest
Sample - ANS-A portion, or part, of the population on interest
Data - ANS-Information collected from the population
Qualitative Variable - ANS-When an object or individual is observed and recorded as a nonnumeric
characteristic.
-we usually count the number of observations for each category and determine what percent are in
each category
Examples of qualitative variables - ANS-gender, beverage preference, type of vehicle owned, state of
birth, eye color, brand of PC, Marital status, hair color
Quantitative Variable - ANS-When a variable can be reported numerically
-either discrete or continuous
Examples of quantitative variables - ANS-balance in your checking account, the ages of company
presidents, the life of a car batter (such as 42 months), number of people employed by a company
, Discrete Variables - ANS-Can assume only certain values, and there are "gaps" between the
values..typically counted
Discrete Variable Examples - ANS-Number of bedrooms in a house (1,2,3,4, etc), number of cars arriving
at Exit 25 by Disney in an hour, number of students in each section of a statistics course. (a home can
have 3 or 4 bedrooms but it can not have 3.56 bedrooms), children in a family, strokes on a golf hole, TV
sets owned
Continuous Variable - ANS-Can assume any value within a specific range...result from measuring
Continuous Variable Example - ANS-air pressure in a tire and the weight of a shipment of tomatoes,
number of ounces of raisins in a box of raisin bran cereal, duration of flights from Orlando to San Diego,
GPA of a particular student could be 3.257633 but the usual practice is to round 3 places, Amount of
income tax paid, weight of a student, yearly rainfall in Tampa, FL
Nominal Data - ANS-Represented as labels or names. They have no order. They can only be classified an
counted. We are limited to to counting the number in each category of the variable
Examples of Nominal Data - ANS--Classification of the 6 colors of M&M milk chocolate candies because
classifying by color, not by order
-Variable gender, counting number of students entering a football game with a student ID and report
how many are women and how many are women
-Jersey numbers of football players, make of a car
Ordinal Data - ANS-Based on a relative ranking or rating of items based on a defined attributive or
qualitative variable. Only ranked or counted. An important characteristic of using a relative scale is that
we cannot distinguish the magnitude of difference between "superior" and "good" is the same as
difference between "poor" and "superior"
Examples are Ordinal Data - ANS--Top ten states for a business climate based on an evaluation of over
20 factors, the states are ranked in order from best to worst climate
-"Overall, how do you rate the quality of instruction in this class?" a students response is recorded on a
relative scale of inferior, poor, good, excellent, and superior.
-your rank in class, team standings in the Pac-10
Interval Data - ANS-The interval or the distance between values is meaningful. Based on a scale with a
known unit of measurement.
Interval Data Example - ANS--Fahrenheit scale, suppose high temperatures on 3 consecutive winter days
in Boston are 28, 31, and 20 degrees F, these temps can be easily ranked, buy we can also determine
interval or distance between temps, can between 10 and 15 degrees and 50 and 55 but 0 is just a point
on the scale. it does not represent the absence of heat or cold.(by our own measurement scale it is
cold)we can not make statements similar to 20 degrees F is twice as warm as 10 degrees.
-women's dress sizes, IQ (intelligence scale), SAT scores.
Ratio-Level Data - ANS-"highest level of measurement", based on a scale with a known unit of
measurement and a meaningful interpretation of of zero on the scale
