Reliability in Research: Understanding Sources of Error

In research, reliability refers to the consistency or stability of measurements over time. However, there are several sources of error that can threaten this reliability, making it essential for researchers to be aware of these factors.

One of the primary sources of error is participant changes. These changes can occur due to various factors such as focus/attention affecting reaction times or hunger/tiredness leading to reduced physical/mental performance. While shortening the time between measurements can reduce this potential for change, it is not always possible to eliminate it entirely. For instance, even two closely timed measurements may be affected by environmental conditions such as light, day, time, and temperature.

Another significant source of error is environmental changes. These changes can occur during the measurement process or over a longer period, influencing the results. For example, small environmental changes, such as variations in lighting or noise levels, can affect the accuracy of measurements taken using instruments like stopwatches.

Human error is also a critical factor in reliability. This includes not only errors made by researchers but also differences in human perception and judgement. Even when a measurement process is considered precise, human judgement is often involved in its use. For instance, determining when to start and stop the stopwatch can introduce errors due to researcher bias or fatigue.

During the dissertation process, researchers are responsible for taking measurements, which makes them prone to introducing error. Some of the common sources of error in dissertations include researcher error, environmental changes, and participant changes. These factors can lead to instability or inconsistency in measurement outcomes, highlighting the importance of recognizing threats to reliability.

In conclusion, understanding the sources of error is crucial for ensuring the reliability of research measurements. By acknowledging the potential for participant changes, environmental changes, human error, and other factors that can affect reliability, researchers can take steps to minimize these errors and produce more accurate results.

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