OPRE 6301 TEST 2 EXAM QUESTIONS
AND ANSWERS 2026 VERIFIED.
Methods of collecting data - ANS direct observation
experiments
surveys- solicits information from people
why we take samples - ANS To contact the whole population would be time consuming
The cost of studying all the items in a population may be prohibitive
The physical impossibility of checking all items in the population
The destructive nature of some tests
The sample results are adequate
*simple random sample - ANS each item or person in the population has the same chance of
being included
@2026/2027 ALLRIGHTS RESERVED.
,names of 25 employees being chosen out of a hat from a company of 250 employees
*systematic random sampling - ANS The items or individuals of the population are arranged
in some order. A random starting point is selected and then every kth member of the population
is selected for the sample.
A population consists of 845 employees of Nitra Industries. A sample of 52 employees is to be
selected from that population.
First, k is calculated as the population size divided by the sample size. For Nitra Industries, we
would select every 16th (845/52) employee list. If k is not a whole number, then round down.
Random sampling is used in the selection of the first name. Then, select every 16th name on
the list thereafter
*stratified random sampling - ANS A population is first divided into subgroups, called strata,
and a sample is selected from each stratum
Useful when a population can be clearly divided in groups based on some characteristics
If we only have sufficient resources to sample 400 people total, we would draw 100 of them
from the low income group...
*cluster sampling - ANS A population is divided into clusters using naturally occurring
geographic or other boundaries. Then, clusters are randomly selected and a sample is collected
by randomly selecting from each cluster.
Subdivide the state into small units—either counties or regions, then take samples of the
residents in each of these regions and interview them.
@2026/2027 ALLRIGHTS RESERVED.
, sample size - ANS The number of subjects used in an experiment or study
the larger the better
*sampling error - ANS differences between the sample and the population that exist only
because of the observations that happened to be selected for the sample
increasing sample size will reduce this error
*nonsampling error - ANS more serious and are due to mistakes made in the acquisition of
data or due to the sample observations being selected improperly
Errors in data acquisition
Nonresponse errors
Selection bias
increasing sample size will not reduce this error
*errors in data acquisition - ANS recording of incorrect responses, due to:
— incorrect measurements being taken because of faulty equipment,
— mistakes made during transcription from primary sources,
— inaccurate recording of data due to misinterpretation of terms, or
— inaccurate responses to questions concerning sensitive issues
@2026/2027 ALLRIGHTS RESERVED.
AND ANSWERS 2026 VERIFIED.
Methods of collecting data - ANS direct observation
experiments
surveys- solicits information from people
why we take samples - ANS To contact the whole population would be time consuming
The cost of studying all the items in a population may be prohibitive
The physical impossibility of checking all items in the population
The destructive nature of some tests
The sample results are adequate
*simple random sample - ANS each item or person in the population has the same chance of
being included
@2026/2027 ALLRIGHTS RESERVED.
,names of 25 employees being chosen out of a hat from a company of 250 employees
*systematic random sampling - ANS The items or individuals of the population are arranged
in some order. A random starting point is selected and then every kth member of the population
is selected for the sample.
A population consists of 845 employees of Nitra Industries. A sample of 52 employees is to be
selected from that population.
First, k is calculated as the population size divided by the sample size. For Nitra Industries, we
would select every 16th (845/52) employee list. If k is not a whole number, then round down.
Random sampling is used in the selection of the first name. Then, select every 16th name on
the list thereafter
*stratified random sampling - ANS A population is first divided into subgroups, called strata,
and a sample is selected from each stratum
Useful when a population can be clearly divided in groups based on some characteristics
If we only have sufficient resources to sample 400 people total, we would draw 100 of them
from the low income group...
*cluster sampling - ANS A population is divided into clusters using naturally occurring
geographic or other boundaries. Then, clusters are randomly selected and a sample is collected
by randomly selecting from each cluster.
Subdivide the state into small units—either counties or regions, then take samples of the
residents in each of these regions and interview them.
@2026/2027 ALLRIGHTS RESERVED.
, sample size - ANS The number of subjects used in an experiment or study
the larger the better
*sampling error - ANS differences between the sample and the population that exist only
because of the observations that happened to be selected for the sample
increasing sample size will reduce this error
*nonsampling error - ANS more serious and are due to mistakes made in the acquisition of
data or due to the sample observations being selected improperly
Errors in data acquisition
Nonresponse errors
Selection bias
increasing sample size will not reduce this error
*errors in data acquisition - ANS recording of incorrect responses, due to:
— incorrect measurements being taken because of faulty equipment,
— mistakes made during transcription from primary sources,
— inaccurate recording of data due to misinterpretation of terms, or
— inaccurate responses to questions concerning sensitive issues
@2026/2027 ALLRIGHTS RESERVED.
