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Portage Statistics Cnsl 503 Module 3 Stats Questions And Answers With Complete Solutions | New Update 2026

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Portage Statistics CNSL 503 Module 3 Stats QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS | NEW UPDATE 2026

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Portage Statistics CNSL 503 Module 3 Stats QUESTIONS AND
ANSWERS WITH COMPLETE SOLUTIONS | NEW UPDATE 2026



What is the difference between a parameter and a statistic? - (answer)A parameter is a numerical value
that describes a population, such as the population mean. A statistic is a numerical value that describes a
sample, such as a sample mean



A statistic is a descriptive statistical result that is generated from a sample, whereas a parameter is a
statistical result from a population..



Why is it important to have a representative sample? - (answer)It is important to have a representative
sample, because we're trying to make inferences about a certain population. In order to make correct
inferences about this population, the sample must reflect the population. For instance, not having a
representative sample is what called Literary Digest to predict Alf Landon to win, when FDR actually won
in a land slide.



Representative sample - (answer)consists of members that possess the same characteristics as those of
the population

(e.g. age distribution)



biased sample - (answer)a sample that is not representative of the population



simple random sampling - (answer)-every member of the population has an equal chance of being
selected for the sample

-the probability that each member is selected is independent of one another

-computers are often used to generate random numbers

-best for small sample sizes



systematic sampling - (answer)random sampling with a system in which the starting point is random and
each subsequent member selected is based on a fixed interval (e.g. every 3rd person)

- the probability that each member is selected is not independent of one another

-random samples can be achieved in a way that is more efficient than simple random samlping

, Portage Statistics CNSL 503 Module 3 Stats QUESTIONS AND
ANSWERS WITH COMPLETE SOLUTIONS | NEW UPDATE 2026



stratified sampling - (answer)is when you divide the population into strata (typically based on age,
gender, race, socioeconomic status) and then you randomly select people to sample from each strata



(not everyone in a strata is studied)



-great for populations with subsections/ different characterstics



cluster sampling - (answer)is when you divide the population into clusters such as the U.S. voters into
voters by states, and then you randomly select clusters (e.g. CA, NY, KY). From there, everyone in that
cluster is studied.



-great for very large populations



convenience sampling - (answer)selecting a sample that is convenient and easy to access

- asking everyone in a lecture hall to determine L handedness at your school

-does NOT result in a representative sample

-generally is more prone to bias than other sampling methods



Wha is sampling error ? - (answer)Sampling error is the difference between the population parameter
and the sample statistic. It is impossible to eliminate sampling error but there are ways to reduce it such
as a larger sample size.



How to reduce sampling error? - (answer)Increase the sample size or use STRATIFIED sampling (increase
the likelihood that the sample is more representative of the population)



- the larger the sampling size the smaller the sampling error



What are non-sampling errors? aka as?

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