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CNSL 503 Module 3 – 2026 Exam Questions, Practice Questions with 100% Correct Answers | Complete Exam Review Material

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This document contains exam-style questions and answers for CNSL 503 Module 3, covering key statistical concepts such as sampling methods, sampling error, bias, the Central Limit Theorem, standard error, probability, hypothesis testing, statistical significance, p-values, and Type I/II errors. It is structured as a concise question-and-answer study guide designed for exam preparation. The material serves as a quick revision resource covering core definitions and concepts commonly tested in the module. Keywords Sampling methods Simple random sampling Stratified sampling Cluster sampling Systematic sampling Convenience sampling Sampling error Non-sampling error Selection bias Measurement bias Response bias Sampling distribution Central Limit Theorem Standard error Probability Relative frequency Statistical significance Hypothesis testing Null hypothesis Alternative hypothesis Critical value Alpha level Type I error Type II error P-value Exam revision Statistics Research methods

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Module 3 CNSL 503 2026 Exam
Questions with 100% Correct
Answers | Latest Update



5 types of Samples - ANSWER ✔✔Simple Random- every member

of the population has an equal chance of being selected




Stratified- population can be divided into subgroups called strata, and

randomly gathering data from those subgroups

, Cluster- dividing a population into subgroups known as clusters and then

randomly selecting several groups (clusters) for the study




Systematic- establishing a rule for how sample members will be selected




Convenience - selecting individuals because they just happen to be at a

certain place


Sample Error vs Non-Sampling Error - ANSWER ✔✔Sampling Error-

any deviation between the parameter and statistic




^^Eliminate by increasing sample size




Non-Sampling or sample bias- the researcher has made a mistake in the

data collection


Three types of Bias - ANSWER ✔✔Measurement: misleading

questions on a survey

Response: response to surveys with inaccurate responses

Selection: not a truly representative sample of the population

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