Foofy asks a sample of students their choice in the election for class president. concludes that Poindexter will win. It turns out that Dorcas wins. What is the statistical explanation for Foofy’s erroneous prediction?

Need to ask questions first to get more details.

Was the sample random? Was it large enough? Was the spread statistically significant? Was the way the question was stated biased?

The statistical explanation for Foofy's erroneous prediction can be attributed to sampling error.

Sampling error occurs when the sample taken to make predictions or draw conclusions from a larger population does not accurately represent the characteristics or the diversity of the population. In Foofy's case, the sample of students that was surveyed might not have been truly representative of the entire population of students who were eligible to vote.

For example, if the sample of students surveyed was not randomly selected or if certain groups of students were over-represented or under-represented, it can lead to biased results. It is possible that the preferences of the students surveyed were not reflective of the preferences of the entire student body.

Another possible factor could be a small sample size. If the sample size is too small, it increases the likelihood of getting results that do not accurately reflect the population. In this case, if Foofy only surveyed a small number of students, the results might have been influenced by random chance rather than being a true reflection of the overall preferences.

Therefore, due to sampling error, Foofy's prediction based on the sample of students was inaccurate, and the actual outcome of the class president election was different from what was initially concluded.

The statistical explanation for Foofy's erroneous prediction can be attributed to a sampling error. Foofy asked only a sample of students about their choice for class president, which means that the individuals in the sample may not be representative of the entire student population. This discrepancy between the sample and the population is known as sampling bias.

If the sample used by Foofy was not randomly selected, there could be a bias in the selection of students. For example, Foofy might have asked only students from a specific grade or those who were more vocal about their preferences. In such cases, the sample may not accurately reflect the diversity of the entire student body and can lead to erroneous predictions.

Additionally, it is possible that the sample used by Foofy was too small or not sufficiently varied, which can further contribute to inaccurate conclusions. The larger the sample size and the more diverse the sample, the more likely it is to accurately represent the population and yield accurate predictions.

Therefore, Foofy's erroneous prediction can be attributed to sampling bias, where the sample used was not representative of the entire student population, leading to misleading results. To avoid such errors in the future, it's important to ensure the sample selection is random, diverse, and large enough to increase the likelihood of making accurate predictions.