Question

Indicate whether we should trust the results of the study. Is the method of data collection biased? If it is, explain why. Send an email to a random sample of students at a university asking them to reply to the question: "Do you think this university should fund an ultimate frisbee team?" A small number of students reply. Use the replies to estimate the proportion of all students at the university who support this use of funds.

Short answer

The results of this study should not be fully trusted due to possible response bias. The method of data collection is biased as it may mostly represent the opinions of the students who have strong feelings about the subject.

Step-by-step solution

Analyze the data collection method

In this case, an email was sent to a random sample of students at the university asking for their opinion on funding an ultimate frisbee team. A small number of students reply. Consider the fact that not all students might have seen the email or chosen to respond, which might introduce a bias in the data collected.

Identify probable bias

There is potential for response bias here. The students who did respond are more likely to have a strong opinion about the subject matter either for or against. Hence, these responses might not represent the opinions of all the students at the university, but rather of those with stronger sentiment regarding the subject.

Determine validity of results

Because the sample of students who responded to the email could be biased towards those with a strong opinion about the issue, it would not be correct to generalize their responses to all students in the university. Hence, it would be considered unwise to trust the study results or use them for estimating the opinion of the entire student population.

Key concepts

Understanding Response Bias

When conducting research or collecting data, obtaining accurate and unbiased information is crucial to ensure valid study results. One common challenge researchers face is response bias. This type of bias occurs when participants in a study provide answers that are not reflective of their true thoughts or feelings. Often, response bias is the result of how questions are phrased, the environment in which questions are asked, or the pressure to provide a socially desirable answer.

In the exercise, a small number of students who received the email responded to the question about funding an ultimate frisbee team. The key issue here is that the participants who choose to respond might have stronger opinions about the topic, which could skew the results. For example, students passionate about sports or those strongly against the use of funds could have been more motivated to respond. To improve the reliability of future studies and reduce response bias, researchers can use anonymized surveys, neutral wording, and ensure that respondents understand that all viewpoints are valid and valued.

The Importance of Random Sampling

One of the foundations of any reliable study is a well-executed random sampling technique. Random sampling involves selecting participants for a study in a way that each member of the population has an equal chance of being chosen. This method is crucial for creating a sample that is representative of the entire population, allowing for generalizations to be made from the sample to the population.

However, even with random sampling, the study in the exercise experienced a low response rate, highlighting an essential consideration: a random sample is effective only if the participants chosen also participate. When a significant portion of those sampled chooses not to respond, the random nature of the sample can be compromised, leading to sampling bias. The exercise shows the necessity of not only selecting a random sample but also encouraging participation to ensure the sample accurately reflects the population. Enhancing response rates can be achieved through follow-up communications, incentivizing participation, and making it easy for participants to respond.

Establishing the Validity of Study Results

Ultimately, the validity of study results hinges upon how well a study is designed and executed. Validity refers to the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. The aim is to draw accurate conclusions and to be able to generalize the findings to the broader population.

The exercise revealed potential weaknesses in the study's design, suggesting that the results may not be a trustworthy reflection of the population's views. The issue of a low response rate casts doubt on the representativeness of the data. To ensure validity, future studies should aim for higher response rates through comprehensive sampling strategies and address potential biases that could affect the results. For instance, using multiple methods of reaching out to participants, having a larger sample size, and accounting for non-respondents in the analysis can improve the validity of the study's conclusions.