USING R FOR INTRODUCTORY STATISTICS
2ND EDITION VERZANI SOLUTIONS
MANUAL EXAMINATION TEST 2026
COMPLETE QUESTIONS AND SOLUTIONS
⩥ inferential statistics. Answer: sample statistics used to draw
conclusions about population parameter (larger population)
⩥ samples. Answer: from __________, we compute statistics...
⩥ sample. Answer: a smaller representation of a larger population
⩥ parameters. Answer: anything looking to be described
⩥ variables. Answer: any physical, attitudinal, or behavioral
characteristic that can change and have different levels (i.e. sex, color,
temperament, etc..). there are three specific levels: normal, ordinal, and
scale.
⩥ discrete variable. Answer: takes on only specific values (i.e. names,
categories)
, ⩥ continous variable. Answer: take on a full range of infinite values (i.e.
numbers, decimals); always more than two or three levels
⩥ operationalized. Answer: variables are ______________ so that we
can measure them
⩥ nominal variable. Answer: discrete categories/names as levels, there is
no magnitude (i.e. color: red, white, blue or sex: male vs female)
⩥ ordinal variable. Answer: discrete variables that are rank ordered (i.e.
finish in race: first, second, third or class: freshman, sophomore, etc...)
⩥ scale variable. Answer: variables that are continuous and have
numbers as values; these are most accurate and meaningful (i.e.
temperature: 32, 54, 73 or weight: 102, 130, 203, etc...) *anything scaled
can be ordinal but you lose a little bit of information.
⩥ ratio. Answer: variables that meet the criteria for scale but also have
meaningful zero points (i.e. time running out in a basketball game)
⩥ levels. Answer: discrete values or conditions variables can take on
(i.e. male verse female). *cannot just have one option.
2ND EDITION VERZANI SOLUTIONS
MANUAL EXAMINATION TEST 2026
COMPLETE QUESTIONS AND SOLUTIONS
⩥ inferential statistics. Answer: sample statistics used to draw
conclusions about population parameter (larger population)
⩥ samples. Answer: from __________, we compute statistics...
⩥ sample. Answer: a smaller representation of a larger population
⩥ parameters. Answer: anything looking to be described
⩥ variables. Answer: any physical, attitudinal, or behavioral
characteristic that can change and have different levels (i.e. sex, color,
temperament, etc..). there are three specific levels: normal, ordinal, and
scale.
⩥ discrete variable. Answer: takes on only specific values (i.e. names,
categories)
, ⩥ continous variable. Answer: take on a full range of infinite values (i.e.
numbers, decimals); always more than two or three levels
⩥ operationalized. Answer: variables are ______________ so that we
can measure them
⩥ nominal variable. Answer: discrete categories/names as levels, there is
no magnitude (i.e. color: red, white, blue or sex: male vs female)
⩥ ordinal variable. Answer: discrete variables that are rank ordered (i.e.
finish in race: first, second, third or class: freshman, sophomore, etc...)
⩥ scale variable. Answer: variables that are continuous and have
numbers as values; these are most accurate and meaningful (i.e.
temperature: 32, 54, 73 or weight: 102, 130, 203, etc...) *anything scaled
can be ordinal but you lose a little bit of information.
⩥ ratio. Answer: variables that meet the criteria for scale but also have
meaningful zero points (i.e. time running out in a basketball game)
⩥ levels. Answer: discrete values or conditions variables can take on
(i.e. male verse female). *cannot just have one option.
