Question

Consider each of these situations. Do you think the proposed sampling method is appropriate? Explain. a) We want to know if there is neighborhood support to turn a vacant lot into a playground. We spend a Saturday afternoon going door-to-door in the neighborhood, asking people to sign a petition. b) We want to know if students at our college are satisfied with the selection of food available on campus. We go to the largest cafeteria and interview every 10 th person in line.

Short answer

Neither sampling method is entirely appropriate due to potential bias. They may not fully represent the opinions of the entire population in question.

Step-by-step solution

Assessing Sampling Method for Situation (a)

In situation (a), the proposed sampling method involves going door-to-door in one neighborhood on a Saturday afternoon to gather signatures for a petition regarding converting a vacant lot into a playground. This method can be effective for gauging local support if most residents are home during the survey period. However, it may not provide a complete picture since it could miss people who are not at home or those who do not typically stay in the neighborhood during weekends, thus introducing bias.

Assessing Sampling Method for Situation (b)

In situation (b), interviews are conducted with every 10th person in line at a large cafeteria to gauge student satisfaction with campus food selection. This method may be biased as it only samples those who are present in that specific cafeteria, potentially excluding students who do not frequent that cafeteria or have different food preferences. The timing and location of the sampling could affect the results, hence not representing the entire student body effectively.

Overall Appropriateness

For both situations, while the sampling methods might provide some insights, they are not entirely appropriate for obtaining a representative sample of the entire population in question. Situation (a) could miss diverse views as it focuses on one neighborhood and at one specific time. Situation (b) may miss opinions from students who avoid that specific cafeteria or are absent at the time of sampling, thus leading to biased results.

Key concepts

Bias in Sampling

When collecting data, it's crucial to ensure that the sampling method employed does not introduce bias. Bias occurs when certain groups within a population are over or under-represented. In our exercises, biases are evident in both sampling scenarios:

• In situation (a), the timing and location of the door-to-door survey could exclude individuals who are not at home during the afternoon, such as those working on Saturdays or frequently traveling. This results in missing the opinions of a segment of the neighborhood, leading to potential bias in the findings.
• In situation (b), interviewing every 10th person at a single cafeteria might not represent the full spectrum of culinary preferences among the students, especially if some students prefer other dining facilities or opt for off-campus dining options. This select group might share similar dining habits that do not reflect the overall sentiment of the student body.

To minimize bias, researchers should diversify their data collection approaches and ensure they reach all potential subgroups within the population. This might involve sampling at different times, locations, or using varied methods to capture a truly representative view.

Representative Sample

A representative sample accurately reflects the characteristics of the population from which it is drawn. It's essential for any survey or study to achieve credibility in its results. In the provided exercises, neither sampling method guarantees a truly representative sample due to their inherent limitations.

• In situation (a), only those present in the neighborhood during the weekend are surveyed. This means that the opinions of individuals who are routinely away or traveling, as well as those who might not be engaged in neighborhood affairs, are missing. Ideally, a representative sample would capture inputs from all demographic and socio-economic segments of the neighborhood.
• In situation (b), focusing on a single meal service location at one type of dining facility restricts the feedback to certain dining habits and preferences. A representative survey would incorporate responses from multiple dining venues and times, ensuring that every segment of campus diners is included.

Ensuring a representative sample requires careful planning and execution of the sampling method to include diverse inputs from all relevant parts of the population, thereby enhancing the reliability of the results.

Survey Methodology

Survey methodology is the framework through which data is collected, ensuring that results are valid, reliable, and as free from bias as possible. A well-developed methodology considers various factors, including the who, what, when, where, and how of data collection.

• Who: In situation (a), identifying all resident types in the neighborhood and ensuring they're all given an opportunity to participate would be critical. This means potentially reaching out at varying times or through alternative channels, such as online surveys, to engage those not at home.
• What: Situation (b) requires understanding of the full range of dining options and student preferences. The survey questions should be comprehensive, covering different dining experiences and locations on campus.
• When and Where: Timing and location greatly affect the data collected. Both scenarios illustrate that limiting surveys to certain times and locations can skew data. Expanding the survey to different cafeterias at various times, as in Situation (b), would offer a broader view.
• How: Using a mix of survey methods, such as online forms, face-to-face interviews, and telephonic surveys, can help gather a wide array of participant responses and ensure anyone can participate regardless of their situation at a single point in time.

A thorough consideration of these elements will strengthen the survey's methodology, creating results that are both meaningful and actionable. By overcoming the inherent biases and limitations of the initially proposed methods, the overall accuracy and applicability of the survey findings improve.