What is the difference between a statistic and a parameter? - ANSWER A statistic is a de-
scriptive statistical result that is generated from a sample, whereas a parameter is a statisti-
cal 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. - ANSWER repre-
sentative 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. - ANSWER
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 mem-
ber being selected. - ANSWER 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. - ANSWER 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 - ANSWER Stratified sampling
Two types of stratified sampling: - ANSWER 1. Proportional
2. Non-proportional
1
, Proportional stratified sampling produces a sample that includes - ANSWER similar pro-
portions to the population
Non-proportional stratified sampling gathers equal sample sizes from each group regardless
- ANSWER 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 - ANSWER Cluster sampling
This method of sampling involves establishing a rule for how sample members will be se-
lected (every 10th person, etc) - ANSWER 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
- ANSWER convenience sampling
The type of sampling chosen by a researcher is based on 3 things: - ANSWER 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 - ANSWER sampling error
A large enough ___ should be selected to represent the population to reduce sampling error.
- ANSWER sample size
2
scriptive statistical result that is generated from a sample, whereas a parameter is a statisti-
cal 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. - ANSWER repre-
sentative 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. - ANSWER
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 mem-
ber being selected. - ANSWER 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. - ANSWER 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 - ANSWER Stratified sampling
Two types of stratified sampling: - ANSWER 1. Proportional
2. Non-proportional
1
, Proportional stratified sampling produces a sample that includes - ANSWER similar pro-
portions to the population
Non-proportional stratified sampling gathers equal sample sizes from each group regardless
- ANSWER 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 - ANSWER Cluster sampling
This method of sampling involves establishing a rule for how sample members will be se-
lected (every 10th person, etc) - ANSWER 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
- ANSWER convenience sampling
The type of sampling chosen by a researcher is based on 3 things: - ANSWER 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 - ANSWER sampling error
A large enough ___ should be selected to represent the population to reduce sampling error.
- ANSWER sample size
2
