When a population is studied, any inconsistency produced by the instrument used will result in
- Sampling error
- Measurement error
- Instrumentation error
- Data error
Correct Ans: (B)
Explanation:
In research, accuracy is crucial for reliable results. However, when a measurement instrument (such as a survey, scale, or test) produces inconsistent or inaccurate data, it leads to measurement error. This affects the validity and reliability of research findings.
Measurement error can occur due to several factors:
- Instrument Defects: Faulty survey questions, poorly calibrated tools, or incorrect data entry can introduce errors. If a scale consistently records higher or lower values, it skews results.
- Human Error: Interviewers or respondents may misinterpret questions, leading to incorrect responses. Fatigue, bias, or memory recall issues can also contribute to errors.
- Environmental Factors: External elements like noise, lighting, or distractions during data collection can affect responses, especially in observational studies.
- Data Processing Issues: Errors in data recording, entry, or software miscalculations can distort results, reducing study credibility.
Additionally, measurement error differs from sampling error, which happens when a selected sample does not represent the entire population. While sampling error is related to who is studied, measurement error is linked to how data is collected.
Moreover, minimizing measurement error requires proper instrument design, pre-testing, and calibration. Using standardized tools, clear instructions, and trained data collectors helps ensure data accuracy and consistency.
In conclusion, measurement error results from inconsistencies in data collection instruments, affecting research validity. Researchers must address these issues to maintain reliable findings.