ABSTRACT
Type I error occurs when the null hypothesis is rejected despite being true as a result of statistical testing. Type II error occurs when the null hypothesis is not rejected when it is false because of statistical testing. The 'level of significance' refers to the statistical probability related to type I error. Sensitivity is the ability to identify correctly the people who have the condition under investigation. Specificity refers to the ability to correctly identify those who do not have the condition under investigation. Standard deviation measures the scatter of the normalised data around the mean. Confidence intervals give the probability of a true population mean lying within a range derived from a sample mean and its standard error. The student's t-test is a parametric test based on the t-distribution, and is used for comparing a single small sample with a population, or for comparing the difference in means between two small samples.
