Final answer:
Responses in surveys are weighted to better reflect the general population and yield more accurate results. Pollsters seek random samples to avoid bias, but changes in technology and question design can still affect polling accuracy. Weighting adjusts for underrepresentation and improves the validity of sample statistics.
Step-by-step explanation:
Responses are "weighted" to match demographics like gender, age, education, race, Hispanic origin, region, and population density because these factors can influence how representative a survey or poll is of the general population. For instance, if a survey conducted at the Los Angeles Convention Center for "America's Smithsonian" road show by Intel Corporation doesn't accurately represent all demographic and ethnic groups who would be in attendance, the results could be biased. Weighting adjusts for this by giving more influence to responses from underrepresented groups. Consequently, survey statistics may more accurately reflect true population parameters.
Pollsters interview random people throughout the country when trying to project election outcomes to avoid selection bias and to get a representative sample. Changes in technology, like the shift from landlines to cell phones, have made this sampling more challenging because certain segments of the population are now harder to reach, potentially leading to selection bias.
The design of surveys can limit accuracy. For example, question wording can result in varying responses, revealing the sensitivity of polls to subtle changes. Interviewer characteristics such as gender and race might also introduce interviewer bias, as seen in studies where respondents' answers differed based on these factors.
Thus, accurate polling requires careful consideration of demographics, question design, and technological challenges to ensure a representative sample and valid results. Without such considerations, response bias and other inaccuracies could misrepresent the public opinion or trends being studied.