CNSL 503 Final Exam Questions and Answers 2025
CNSL 503 Final Exam Questions and
Answers 2025
Statistic. – ANSWER. A numerical value that is generated from the individual
scores in the dataset of a sample.
Parameter – ANSWER. A numerical value generated from the individual scores in
the dataset of the entire population. Remember this saying: statistic = sample;
parameter = population.
Representative sample – ANSWER. Composed of members that generally
possess the same characteristics as those of the population.
Random sampling - ANSWER. 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 – ANSWER. 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 – ANSWER .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-proportional.
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CNSL 503 Final Exam Questions and
Answers 2025
Statistic. – ANSWER. A numerical value that is generated from the individual
scores in the dataset of a sample.
Parameter – ANSWER. A numerical value generated from the individual scores in
the dataset of the entire population. Remember this saying: statistic = sample;
parameter = population.
Representative sample – ANSWER. Composed of members that generally
possess the same characteristics as those of the population.
Random sampling - ANSWER. 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 – ANSWER. 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 – ANSWER .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-proportional.
1
