Interpreting results of clinical trials
When interpreting results following clinical trials, researchers must ensure that the subject groups are of a suitable size to reduce the magnitude of experimental error.
A small subject group increases the chance that an unknown factor could affect the result. It is less likely to pick up on variation between individuals. The subject groups need to be of a large enough size in order to have some relevance when applying the data to the wider population.
It is important that subject groups have sufficient diversity so that the results of the trial reflect the population and avoid bias. Care needs to be taken to properly reflect age, gender, ethnicity, class, and geographic spread.
The results from all groups are then compared to determine if there are any statistically significant differences between the results.
When the results of clinical trials are displayed as a graph, they often feature error bars that can help show the spread of data around the mean value. A small error bar means a smaller Standard deviation is an important measure of spread or dispersion. It tells us how far, on average the results are from the mean. from the mean value. Larger bars mean that there is a wider spread of data from the mean value.