The definition of the level of significance is "the probability of making a Type I error when the null hypothesis is true as an equality" (Anderson et al, 2020). An example of a type one error is when the corresponding research claims that the new system that is being tested improves the performance when in fact the new system does not show any improvement over the current system that is being used this is also sometimes called a false positive (mlblevins, 2014). When it comes to sample size the larger sample sizes allows the researcher to increase the significant level of finding. Mean that the larger samples sizes will more accurately mirror the findings of the entire population. On the downside however the higher the sample size the more the resources that will need to be used. Please discuss using references to support.