CNSL 503 EXAM QUESTIONS AND ANSWERS WITH COMPLETE
SOLUTIONS VERIFIED
statistic
numerical value that is generated from the individual scores in the dataset of a sample
Parameter
a numerical value generated from the individual scores in the dataset of the entire population.
Remember this saying: statistic = sample; parameter = population.
representative sample
composed of members that generally possess the same characteristics as those of the population.
Random sampling,
Random sampling, in which every member of the population has an equal chance of being selected,
increases the reliability of the study results. Random sampling is a form of probability sampling, where
each member is independent of the others
Simple random sampling
each individual in the population of size has an equal chance of being selected for the sample. If you
have ever written individual names on separate pieces of paper, placed all the pieces of paper in a hat,
and selected names from the hat, you have conducted simple random sampling
, Simple random sampling relies on chance in order to create a representative sample. It is not practical to
use this method for large populations,
Stratified sampling
a population can be divided into subgroups called strata.
randomly gathering data from subgroups within a sample. Strata such as race, gender, and
socioeconomic status are clearly defined
Stratified sampling is used when the researcher wants to compare outcomes for different subgroups
within a population or to compare outcomes between subgroups. There are two types of stratified
sampling - proportional and non-proportiona
Cluster sampling
dividing a population into subgroups known as clusters and then randomly selecting several groups
(clusters) for the study
For example, suppose you wanted to research nursing students taking graduate statistics. It would be
time-consuming and inefficient to get administrative approval to conduct research on every nursing
student in every college or university. Using cluster sampling, you could identify several colleges and
universities from across the country, obtain administrative approval, and survey each nursing student in
that cluster (college or university).
Cluster sampling is used when participants are spread out geographically, making this form of sampling
more efficient and cost-effective.
SOLUTIONS VERIFIED
statistic
numerical value that is generated from the individual scores in the dataset of a sample
Parameter
a numerical value generated from the individual scores in the dataset of the entire population.
Remember this saying: statistic = sample; parameter = population.
representative sample
composed of members that generally possess the same characteristics as those of the population.
Random sampling,
Random sampling, in which every member of the population has an equal chance of being selected,
increases the reliability of the study results. Random sampling is a form of probability sampling, where
each member is independent of the others
Simple random sampling
each individual in the population of size has an equal chance of being selected for the sample. If you
have ever written individual names on separate pieces of paper, placed all the pieces of paper in a hat,
and selected names from the hat, you have conducted simple random sampling
, Simple random sampling relies on chance in order to create a representative sample. It is not practical to
use this method for large populations,
Stratified sampling
a population can be divided into subgroups called strata.
randomly gathering data from subgroups within a sample. Strata such as race, gender, and
socioeconomic status are clearly defined
Stratified sampling is used when the researcher wants to compare outcomes for different subgroups
within a population or to compare outcomes between subgroups. There are two types of stratified
sampling - proportional and non-proportiona
Cluster sampling
dividing a population into subgroups known as clusters and then randomly selecting several groups
(clusters) for the study
For example, suppose you wanted to research nursing students taking graduate statistics. It would be
time-consuming and inefficient to get administrative approval to conduct research on every nursing
student in every college or university. Using cluster sampling, you could identify several colleges and
universities from across the country, obtain administrative approval, and survey each nursing student in
that cluster (college or university).
Cluster sampling is used when participants are spread out geographically, making this form of sampling
more efficient and cost-effective.
