Question

prior to a mayoral election, a newspaper conducted a poll. the paper surveyed a random sample of registered voters stratified by political party, age, sex, and area of residence. this poll predicted that candidate a would win the election with 52% of the vote. the newspaper was wrong: candidate a lost, getting only 46% of the vote. do you think the newspaper's faulty prediction is more likely to be a result of bias or sampling variability? explain. (multiple choice) (1 pt) a) the faulty prediction was more likely to be the result of sampling error. the description of the sampling method suggests that it will systematically produce samples that aren't representative of the voting population. b) the faulty prediction was more likely to be the result of bias. the description of the sampling method suggests that it will systematically produce samples that aren't representative of the voting population. c) the faulty prediction was more likely to be the result of sampling error. while the sampling method suggests that the sample obtained would be representative of the voting population, random chance in selecting the individuals who were polled means that sample statistics could vary from the population parameter. d) the faulty prediction was more likely to be the result of bias. the question posed to the voters may have pushed them to be more predisposed to say that they would vote for candidate a in the election.

Answer 1

The faulty prediction is more likely to be a result of sampling error and the correct option is C.

Reasoning:

Stratified sampling: The newspaper used a stratified sample, ensuring representation of key demographics in the voting population. This reduces bias compared to a random sample without stratification.

Question-wording: No information suggests biased question wording pushing voters towards candidate A.

Systematic bias: The description doesn't suggest any systematic issue in the sampling method that would consistently favor or disfavor a specific candidate.

Sampling error: Even with a good sampling method, random chance during sample selection can lead the sample to be slightly different from the population. This natural variability can explain the discrepancy between the prediction and the actual results.

Therefore, while bias is always a possibility, the available information points towards sampling error as the more likely explanation for the inaccurate prediction.