University:
University of the People
Course:
HS 4510 | Biostatistics
Academic year:

2024
Views:

54

Pages:

2
Author:

amrinderjeet kaur

UNIT 3 LEARNING JOURNAL Concept of Error Any measurement or research procedure involves some degree of error, which compromises the precision and dependability of the findings. Errors can come from a variety of causes in scientific research and data collection, and they can be categorized into distinct types according to their traits and effects. Systematic Error vs. Random Error Systematic Error: Also called bias, systematic errors impact measurement accuracy and consistently occur in the same direction. These mistakes are frequently brought on by observer bias, defective equipment, or errors in the experiment's design. Systematic mistakes may frequently be detected and fixed by calibration, appropriate experimental controls, and enhanced techniques because they are predictable (Altman & Bland, 1994). Among the examples are: An incorrectly calibrated thermometer that routinely registers temperatures 2°C higher than the true value. a survey question that is formulated to sway respondents' answers, producing data that is skewed. Random errors, often called chance mistakes, are unpredictable changes that arise from intrinsic variability in measurement processes. Unlike systematic errors, which follow a definite pattern, random errors affect the precision of outcomes rather than their correctness. These errors can be reduced by increasing the sample size, repeating observations, and using statistical techniques to take variability into account (Gore, 1981). Examples include: environmental influences that cause small variations in readings, such as small variations in room temperature that have an impact on an electronic balance. Human reaction times vary when a stopwatch is manually stopped. Minimizing Errors in Research Careful study design and data gathering procedures can reduce both systematic and random errors: Researchers should make sure that devices are properly calibrated, employ double-blind study designs, and constantly follow established protocols to prevent systematic errors. Increasing the number of observations, averaging several measurements, and applying statistical corrections can all help increase precision when dealing with random mistakes. Interpreting research results and drawing trustworthy conclusions require an understanding of the distinction between systematic and random errors. Researchers can improve the validity and dependability of their studies and eventually produce more precise and significant scientific findings by successfully resolving these mistakes. REFERENCES: ● Altman, D. G., & Bland, J. M. (1994). Diagnostic tests. 1: Sensitivity and specificity. BMJ, 308(6943), 1552. https://doi.org/10.1136/bmj.308.6943.1552 ● Gore, S. M. (1981). Biostatistics and the medical research council. British Medical Journal, 282(6262), 1307-1311. https://doi.org/10.1136/bmj.282.6262.1307