ABSTRACT
Concerning statistical analysis, which statement below is true?
A Type I error accepts the false null hypothesis (e.g., false negative). A benefit is missed when it was there to be found.
A Type II error is the incorrect rejection of a true null hypothesis (e.g., false positive). A benefit is perceived when really there is none.
A Null hypothesis is a statement of no significant difference or effect.
Specificity (true negative rate) measures the proportion of positives that are correctly identified as such (e.g., the percentage of people with a disease who are correctly identified as having the disease).
Sensitivity (true positive rate) measures the proportion of negatives that are correctly identified as such (e.g., the percentage of healthy individuals who are correctly identified as not having the disease).
