When reviewing student data, a data analyst calculates course pass rates across the entire student population in two ways: once for students in academic support programs and once for students not utilizing academic support. What would be an example of a factor creating a bias in this example?
Question
When reviewing student data, a data analyst calculates course pass rates across the entire student population in two ways: once for students in academic support programs and once for students not utilizing academic support. What would be an example of a factor creating a bias in this example?
Solution 1
In this scenario, a potential source of bias could be the self-selection bias. This bias could occur if students who choose to utilize academic support programs are inherently different from those who do not. For example, students who seek out academic support might be more motivated or might struggle more with the course material than those who do not seek support. These inherent differences, rather than the academic support itself, could be influencing the pass rates. This would make it difficult to accurately determine the effect of academic support programs on pass rates.
Solution 2
One potential source of bias in this example could be the self-selection bias. This bias occurs when individuals select themselves into a group, causing a biased sample. In this case, it's possible that students who choose to utilize academic support programs are inherently different from those who do not. For example, they might be more motivated or have different learning styles, which could affect their course pass rates. This would make it difficult to directly compare the two groups, as the difference in pass rates might be due to these inherent differences rather than the effect of the academic support programs.
Similar Questions
A college needs to report its overall student retention rates to a local newspaper. They reported a 90% retention rate based on senior graduation the previous year. Which statement is true?The college reported an unbiased statistic because they had data on all seniors.The college reported an unbiased statistic because they have a high retention rate.The college reported a biased statistiic because they didn't include all student data.The college reported a biased statistic because 10% of seniors didn't graduate last year.
A researcher is conducting a study on the effectiveness of a new educational program. They only report results from the group of participants who showed the most improvement and ignore the results from the rest of the participants. Which of the following best describes the type of bias this researcher has engaged in?Question 1Answera.P-hackingb.Sampling biasc.Cherry-pickingd.None of the above
A data analyst is analyzing fruit and vegetable sales at a grocery store. They’re able to find data on everything except red onions. If they exclude red onions from the analysis, this would be an example of creating or reinforcing bias.1 pointTrueFalse
Which statement is not correct about data bias?A.Occurs when data or information is limited in some wayB.Painting an inaccurate representation of the populationC.Use complex or opaque algorithmsD.Does not convey the full storyE.Certain elements of a dataset are overweighted or overrepresented
A college IT department needs to reduce the number of computers on campus for student use. How could a data analyst help identify a solution to this problem?1 pointAnalyze the number of classes schedules across all classroomsAnalyze the utilization of the computer labs on campusAnalyze data on the number of students enrolledAnalyze the square footage of all computer labs on campus
Upgrade your grade with Knowee
Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.