CNSL 503: A GUIDE TO A+. QUESTIONS AND ANSWERS
FORMAT.LATEST UPDATE
What is the difference between a statistic and a parameter?
A statistic is a descriptive statistical result that is generated from a sample, whereas a parameter is a
statistical result from a population.
A ___ sample is composed of members that generally possess the same characteristics as those of the
population. They allow for accurate inferences to be made.
representative sample
A ___ sample is not representative of the population. It is attributed to the researcher and data
collection methods, and do not allow for accurate inferences to be made.
biased
This method of sampling is when every member of the population has an equal chance of being
selected, this increases the reliability of results. Each member is independent of the others: selecting
one member does not increase or decrease the likelihood of another member being selected.
Random sampling
This method of sampling is when each individual in the population of size has an equal chance of
being selected for the sample, and relies on chance to create a representative sample. This is NOT
feasible for large populations.
Simple random sampling
This method of sampling is a type of random sampling when populations can be subdivided into
groups called strata. It randomly gathers data from subgroups within a sample. It is used when
researchers wants to compare outcomes for different subgroups within a population or to compare
outcomes within subgroups
Stratified sampling
Two types of stratified sampling:
1. Proportional
2. Non-proportional
Proportional stratified sampling produces a sample that includes
similar proportions to the population
Non-proportional stratified sampling gathers equal sample sizes from each group regardless
of proportional stability
, This method of sampling divides a population into subgroups known as clusters and then randomly
selects several for the study. It is used when participants are geographically spread out as it is more
efficient and cost effective
Cluster sampling
This method of sampling involves establishing a rule for how sample members will be selected (every
10th person, etc)
Systematic sampling
This method of sampling does not result in a representative sample as it involves selecting individuals
based on them happening to be in a certain place, this can result in sampling bias
convenience sampling
The type of sampling chosen by a researcher is based on 3 things:
1. nature of study
2. characteristics of the population
3. size of the sample needed
The nature of random sampling is that the sample statistics will deviate somewhat from the
population parameters, resulting in
sampling error
A large enough ___ should be selected to represent the population to reduce sampling error.
sample size
An error that is not due to sampling, like due to data collection or measurement, is called
non-sampling error
___ bias results from poorly worded/misleading questions or technical errors in a survey
Measurement bias
___ bias results when participants respond inaccurately, untruthfully, or with exaggerated answers.
Response bias
__ bias is when those who participate are not truly a representative sample of the population
Selection bias
Biases are important to recognize because
they affect the result of the study
Researchers should report any known biases in a final study report so
readers can determine reliability
FORMAT.LATEST UPDATE
What is the difference between a statistic and a parameter?
A statistic is a descriptive statistical result that is generated from a sample, whereas a parameter is a
statistical result from a population.
A ___ sample is composed of members that generally possess the same characteristics as those of the
population. They allow for accurate inferences to be made.
representative sample
A ___ sample is not representative of the population. It is attributed to the researcher and data
collection methods, and do not allow for accurate inferences to be made.
biased
This method of sampling is when every member of the population has an equal chance of being
selected, this increases the reliability of results. Each member is independent of the others: selecting
one member does not increase or decrease the likelihood of another member being selected.
Random sampling
This method of sampling is when each individual in the population of size has an equal chance of
being selected for the sample, and relies on chance to create a representative sample. This is NOT
feasible for large populations.
Simple random sampling
This method of sampling is a type of random sampling when populations can be subdivided into
groups called strata. It randomly gathers data from subgroups within a sample. It is used when
researchers wants to compare outcomes for different subgroups within a population or to compare
outcomes within subgroups
Stratified sampling
Two types of stratified sampling:
1. Proportional
2. Non-proportional
Proportional stratified sampling produces a sample that includes
similar proportions to the population
Non-proportional stratified sampling gathers equal sample sizes from each group regardless
of proportional stability
, This method of sampling divides a population into subgroups known as clusters and then randomly
selects several for the study. It is used when participants are geographically spread out as it is more
efficient and cost effective
Cluster sampling
This method of sampling involves establishing a rule for how sample members will be selected (every
10th person, etc)
Systematic sampling
This method of sampling does not result in a representative sample as it involves selecting individuals
based on them happening to be in a certain place, this can result in sampling bias
convenience sampling
The type of sampling chosen by a researcher is based on 3 things:
1. nature of study
2. characteristics of the population
3. size of the sample needed
The nature of random sampling is that the sample statistics will deviate somewhat from the
population parameters, resulting in
sampling error
A large enough ___ should be selected to represent the population to reduce sampling error.
sample size
An error that is not due to sampling, like due to data collection or measurement, is called
non-sampling error
___ bias results from poorly worded/misleading questions or technical errors in a survey
Measurement bias
___ bias results when participants respond inaccurately, untruthfully, or with exaggerated answers.
Response bias
__ bias is when those who participate are not truly a representative sample of the population
Selection bias
Biases are important to recognize because
they affect the result of the study
Researchers should report any known biases in a final study report so
readers can determine reliability
