In advance of the 1936 Presidential Elections, a magazine titled Literary Digest released the results of an opinion poll predicting that the republican candidate Alf Landon would win by a large margin. The magazine send post cards to approximately 10,000,000 prospective voters. These prospective voters were selected from the subscription list of the magazine, from automobile registration lists, from phone lists, and from club membership lists. Approximately 2,300,000 people returned the postcards.
a. Think about the state of the United States in 1936. Explain why a sample chosen from magazine subscription lists, automobile registration lists, phone books, and club membership lists was not representative of the population of the United States at the time.
b. What effect does the low response rate have on the reliability of the sample?
c. Are these problems examples of sampling error or non sampling error?
d. During the same year, George Gallup conducted his own poll of 30,000 prospective voters. His researchers used a method called "quota sampling" to obtain survey answers from specific subsets of the population. Quota sampling is an example of which sampling method described in this module?
Someone may be able to check your answers.
In advance of the 1936 Presidential Election, a magazine titled Literary Digest released the results of an opinion poll predicting that the republican candidate Alf Landon would win by a large margin. The magazine sent post cards to approximately 10,000,000 prospective voters. These prospective voters were selected from the subscription list of the magazine, from automobile registration lists, from phone lists, and from club membership lists. Approximately 2,300,000 people returned the postcards.
d-stratified
a. In 1936, the United States had a highly diverse population, both culturally and socioeconomically. The sample chosen from magazine subscription lists, automobile registration lists, phone books, and club membership lists would not be representative of the entire population for several reasons.
First, magazine subscription lists primarily attract certain demographics, such as readers interested in specific topics or those with disposable income to spend on subscriptions. This would exclude large segments of the population who may not be interested in or afford magazine subscriptions.
Second, automobile registration lists and phone books were more likely to include individuals who owned cars or had telephone lines, which were not yet widely accessible to everyone in the 1930s. This would exclude those from lower-income households or rural areas where these amenities were less common.
Lastly, club membership lists tend to represent individuals who have the means and leisure to participate in organized clubs or associations. This would exclude individuals who may have different interests or financial constraints that prevent them from joining clubs.
Therefore, the sample chosen from these sources would not be representative of the entire United States population, as it would not include a diverse range of socioeconomic backgrounds, geographical locations, and interests.
b. The low response rate from the postcards has a significant effect on the reliability of the sample. In this case, only approximately 2,300,000 out of the 10,000,000 prospective voters returned the postcards, resulting in a response rate of 23%. This low response rate introduces a potential bias, as those who chose not to respond may have different opinions or characteristics from those who did. The sample would be skewed towards individuals who were more motivated or had stronger opinions, which can distort the overall findings and make them less representative of the population.
c. The problems described here are examples of non-sampling error. Non-sampling errors occur when there are flaws or biases in the data collection process that are unrelated to random sampling. In this case, the selection of the sample from certain sources excluded a significant portion of the population, leading to a biased representation of the population. The low response rate further adds to the non-sampling error, as it introduced a potential bias based on the characteristics of those who chose or did not choose to respond.
d. The sampling method described as "quota sampling" is an example of non-probability sampling. In quota sampling, researchers select participants based on specified quotas to ensure that different subgroups of the population are adequately represented in the sample. This method allows researchers to control the composition of the sample based on predetermined criteria, rather than relying on random sampling. However, it should be noted that quota sampling still has limitations and potential biases, as it depends on the researchers' judgment and may not fully represent the underlying population.