Question

Five randomly selected university students are found to be taller than 6 feet. The researchers concluded that the average height of a university student is greater than 6 feet. This result is likely to be skewed because of ___________ a. experimental error b. sampling error c. a subjective opinion

Short answer

The result is likely skewed due to sampling error.

Step-by-step solution

Understanding the Problem

The exercise presents a scenario where the heights of five university students, all taller than 6 feet, are used to conclude that the average height of all university students is greater than 6 feet. We need to determine why this conclusion might be incorrect.

Identify the Concepts

The question hints at biases or errors that can lead to incorrect conclusions. We need to decide if the problem indicates an issue with experimental error, sampling error, or subjective opinion. Each option represents a different type of bias or problem that can affect research conclusions.

Explore Experimental Error

Experimental error refers to inaccuracies that occur during the actual experimental process, often due to faulty equipment or procedures. In this scenario, the selection of students isn't affected by experimental protocols or equipment, so experimental error is not the correct answer.

Assess Sampling Error

Sampling error arises when a sample does not accurately represent the population from which it was drawn, often due to a small or non-representative sample. The selection of only five students, all taller than 6 feet, is not a large or random enough sample to deduce an average height for all university students. This suggests a sampling error.

Consider Subjective Opinion

Subjective opinion implies a personal belief or bias in interpreting results. While the conclusion may seem subjectively biased due to a non-neutral sample choice, the core issue stems from the inadequate representation of the larger population, which is a sampling error rather than a subjective opinion.

Key concepts

Understanding Experimental Error

Experimental error refers to mistakes or inaccuracies that occur during an experiment. These errors can often be traced back to issues like faulty equipment, incorrect measurements, or unforeseen environmental factors.
Since experimental errors mainly relate to the process and conduct of experiments, they might not always involve human fault, but rather inaccuracies in technique or procedure.
For instance, if a thermometer is inaccurately calibrated, any temperature readings it provides may lead to erroneous conclusions about an experiment's results.
In the context of our initial example with the student heights, experimental error concerns are not applicable since we don't have issues with measurement techniques or equipment that skew the results. Instead, the problem is more about how the sample was chosen rather than how data was collected.

Influence of Subjective Opinion

Subjective opinion in research refers to the personal biases or prejudices of the researcher influencing the outcome. It's critical to remain neutral and objective during research to ensure findings aren't colored by personal views or expectations.
Subjective opinions can arise when a researcher has a specific goal or desired outcome, consciously or subconsciously influencing how they interpret data or decide on methodologies.
This can be mitigated by maintaining rigorous scientific protocols and peer reviewing results.
In the university student height example, subjective opinion isn't the primary issue, though it might feel biased. The researchers might be concluding based on what they hope or expect, but the fundamental flaw is not considering a representative sample of the student body.

Impact of Bias in Research

Bias in research can significantly skew results, leading to incorrect or misleading conclusions. It arises when elements unrelated to the actual data collection systematically influence the research outcome.
Biased results are often the result of poor sampling techniques, like selecting an unrepresentative group of participants, or letting external factors impact the research environment. Effective research requires careful attention to these potential pitfalls.
Addressing bias involves:

• Ensuring samples accurately reflect the larger population.
• Using objective measures and double-blind studies where possible.
• Constantly reviewing methodologies for potential bias points.

In our height example, the core issue lies in sampling error which is a form of bias. The selected students do not represent the entire population; thus, the result is skewed, highlighting the crucial need for a representative sampling to avoid bias in research.