1) The portion of the population selected to participate in a poll is known as the
a. public
b. population
c. deliberative group
d. sample
e. focus group
2) A sample that does not overrepresent any portion of the population and whose responses can therefore be safely generalized to the whole is known as a
a. straw sample
b. non probability sample
c. convenience sample
d. quota sample
e. random sample
3) When a poll has a sample that does not represent all segments of the population, the result is called
a. a systematic random sample.
b. a straw poll
c. sample bias
d. sampling error
e. erroneous data
4) Sampling error refers to
a. a number that indicates within what range the results of a poll are accurate.
b. the number of mistakes made by a pollster.
c. a situation in which a sample is not representative of the larger universe being measured.
d. mistakes made in the recording of response in a poll.
e. a situation in which question wording biases the results.
a b c d
A B C D
1) The portion of the population selected to participate in a poll is known as the sample. To determine the sample, pollsters generally use sampling techniques such as random sampling, stratified sampling, or cluster sampling. Random sampling is one of the most common methods, where individuals are selected randomly from the population, ensuring that each person has an equal chance of being included. This helps to ensure that the sample represents the larger population accurately.
2) A sample that does not overrepresent any portion of the population and whose responses can therefore be safely generalized to the whole is known as a random sample. Random sampling is important in ensuring that the sample is unbiased and representative of the larger population. It involves selecting individuals randomly from the population, without any preference or bias, which helps in minimizing any potential sampling errors.
3) When a poll has a sample that does not represent all segments of the population, the result is called sample bias. Sample bias occurs when certain groups or characteristics are overrepresented or underrepresented in the sample. This can lead to inaccurate or misleading results as the sample may not accurately reflect the views, attitudes, or behaviors of the entire population. To minimize sample bias, it is essential to use appropriate sampling techniques and strive for a representative sample.
4) Sampling error refers to a situation in which a sample is not representative of the larger universe being measured. It is the difference between the results obtained from the sample and the actual values that would have been obtained if the entire population had been surveyed. Sampling error is a natural consequence of having a sample rather than a complete population, and it is a measure of the uncertainty or variation in the estimates. A larger sample size usually reduces sampling error as it provides a more accurate representation of the population. Understanding and accounting for sampling error is crucial in interpreting the results of polls and surveys.