Question

For each of the following studies, identify the source(s) of sampling bias and describe (i) how it might affect the study conclusions and (ii) how you might alter the sampling method to avoid the bias. (a) To study the size distribution of rock cod (Epinephelus puscus) off the coast of southeastern Australia, scientists recorded the lengths and weights for all cod captured by a commercial fishing vessel on one day (using standard hook-and-line fishing methods). (b) A nutritionist is interested in the eating habits of college students and observes what each student who enters a dining hall between 8: 00 A.M. and 8: 30 A.M. chooses for breakfast on a Monday morning. (c) To study how fast an experimental painkiller relieves headache pain residents of a nursing home who complain of headaches are given the painkiller and are later asked how quickly their headaches subsided.

Short answer

Study (a) may over-represent fish more likely to be caught with standard hook-and-line methods; using various fishing techniques over a longer period can reduce bias. Study (b) may not reflect all college students' eating habits; observing at varying times and days or using surveys would help. Study (c) potentially overestimates painkiller effectiveness; a randomized controlled trial would provide a more accurate measure.

Step-by-step solution

Identify Sampling Bias in Study (a)

The sampling bias in study (a) likely comes from the fact that only rock cod caught by a commercial fishing vessel on one day are included, and the data is collected using a standard hook-and-line fishing method. This might result in over-representing the type of fish that are more likely to be caught by this method, while other species or smaller fish could be under-represented. The size distribution could therefore be skewed towards larger fish, as smaller fish might be less likely to be caught with hook-and-line.

Propose an Alternative Sampling Method for Study (a)

To reduce sampling bias, scientists could use a range of fishing methods over a longer period. This would include different sizes and types of fish and represent different days and environmental conditions. An example would be using nets with different mesh sizes and combining hook-and-line methods with other fishing techniques.

Identify Sampling Bias in Study (b)

The sampling bias in study (b) comes from observing students in a narrow timeframe on a specific day. This may not accurately represent the eating habits of all college students because it excludes those who do not eat breakfast at that time or on that day. For instance, students with early classes or those who do not eat breakfast might be under-represented.

Propose an Alternative Sampling Method for Study (b)

To obtain a more representative sample, the nutritionist could extend the observation period to include various times of the day and different days of the week. Additionally, randomly sampling different students on different days or using surveys to understand eating habits could help avoid the bias.

Identify Sampling Bias in Study (c)

The sampling bias in study (c) arises from only including residents who complain of headaches and are available to take the experimental painkiller. This may exclude those who have headaches but do not complain or those who are not willing or able to take the painkiller. The study might overestimate the effectiveness if only those who tend to report pain are included.

Propose an Alternative Sampling Method for Study (c)

To avoid this bias, a randomized controlled trial could be implemented where residents are randomly chosen to receive either the experimental painkiller or a placebo, regardless of whether they have reported a headache. This method would provide a more balanced and representative sample to assess the painkiller's effectiveness.

Key concepts

Sampling Methods

Understanding different sampling methods is crucial to collecting data that can lead to accurate and applicable study conclusions. Different types of sampling methods can be employed based on the objectives and the structure of the population.

For instance, simple random sampling ensures that every member of the population has an equal chance of being selected, which is ideal for achieving a representative sample. In contrast, stratified sampling divides the population into strata, or layers, to ensure that specific subgroups are proportionately represented. Cluster sampling and systematic sampling are other methods that may be used when dealing with large populations or when aiming to reduce the logistical complexities of data collection.

The choice of sampling method can significantly impact the results of a study, as an inadequate method can lead to sampling bias, potentially misinforming the study's conclusions. For instance, in study (a), solely using hook-and-line fishing methods may not encompass the variability of the fish population, leading to over or underestimation of certain fish sizes. By combining various fishing techniques and extending the period of data collection, researchers can mitigate this bias and capture a more accurate picture of the population under study.

Study Design

The study design refers to the overall strategy that researchers choose to integrate the different components of the study in a coherent and logical manner, ensuring that the study effectively addresses the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data.

For example, crossover designs, longitudinal studies, and case-control studies each serve different purposes and are selected based on specific research questions and logistical considerations. A well-designed study should aim to minimize biases and confounding variables to provide reliable results.

Using study (b) as an example, the limited observation window on a Monday morning presents a study design issue that could lead to incorrect generalizations about the eating habits of college students. A robust design would include observations at multiple time points covering the entire week, thereby collecting data that better represents the diverse patterns of students' eating habits.

Representative Sample

A representative sample is a subset of a population that closely mirrors the population as a whole in terms of key characteristics. Achieving a representative sample is vital for generalizing the results of a study to the larger population.

Several factors can influence representativeness, including the size and selection method of the sample. Selection bias occurs when the process of choosing participants distorts how the sample represents the population, which can occur due to non-random selection or other sampling errors.

In study (c), selecting only participants who have complained of headaches leads to a sample that may not represent the overall target population, including those who experience headaches but do not report them. A representative sample for this study would involve selecting participants randomly and possibly stratifying them by certain characteristics, such as age or medical history, to ensure all relevant subgroups are included.

Randomized Controlled Trial

A randomized controlled trial (RCT) is considered the gold standard of study designs for evaluating the efficacy of treatments or interventions. In an RCT, participants are randomly assigned to either the treatment group receiving the intervention or the control group receiving a placebo or standard treatment.

This type of study design helps to eliminate selection bias since the assignment of participants is random, and any differences between groups can be attributed to the intervention rather than other variables. Randomization also fosters the creation of comparable groups, which increases the reliability of the conclusions drawn from the study's results.

As recommended for study (c), implementing an RCT would allow researchers to rigorously test the effectiveness of the experimental painkiller by comparing its effects to that of a placebo, within a randomly selected and thus representative group of participants.