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STATISTICS PORTAGE CNSL 503 PROCTORED ASSESSMENT COMPLETE 2026 UPDATED QUESTIONS AND ANSWERS 100 PERCENT SOLUTION

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STATISTICS PORTAGE CNSL 503 PROCTORED ASSESSMENT COMPLETE 2026 UPDATED QUESTIONS AND ANSWERS 100 PERCENT SOLUTION

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STATISTICS PORTAGE CNSL 503
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STATISTICS PORTAGE CNSL 503 PROCTORED
ASSESSMENT COMPLETE 2026 UPDATED
QUESTIONS AND ANSWERS 100 PERCENT
SOLUTION

◉example of parameter . Answer: population mean


◉statistic . Answer: a value that describes a sample; used to estimate
population parameter


◉example of a statistics . Answer: sample mean


◉In order to make correct inferences about the population, the sample
must... . Answer: reflect the population


◉representative sample . Answer: consist of members that possess the
same characteristics as those of the population


◉biased sample . Answer: a sample that is not representative of the
population

, ◉5 types of sampling techniques . Answer: simple random sampling,
systematic sampling, stratified sampling, cluster sampling, and
convenience sampling


◉simple random sampling . Answer: each member of the population
has an equal chance of being selected for the sample


◉example of simple random sampling . Answer: everyone in the
population of interest rolls a die, everyone rolling a 6 gets selected


◉In simple random sampling, the probability that each member is
selected is ____ of one another. . Answer: independent


◉Simple random sampling is ideal for ____ populations. . Answer:
small


◉systemic sampling . Answer: random sampling with a system in
which a starting point is random and each subsequent member is
selected based on a fixed interval


◉example of systemic sampling . Answer: shoppers at a store, start
with second person entering and survey every 5 shoppers


◉In systemic sampling, the probability that each member is selected is
____of one another. . Answer: dependent

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