Statistics

Question 1

What is type 1 error and type 2 error?

Answer 1

Type I error (false-positive): if an investigator rejects a null hypothesis that is actually true in the population

Type II error (false-negative):occurs if the investigator fails to reject a null hypothesis that is actually false in the population.

Question 2

What is the definition of sensitivity and specificity?

Answer 2

Sensitivity: also called true positive rate; a test’s ability to detect an individual with disease as positive

Specificity: also called true negative rate; a test’s ability to detect an individual who does not have a disease as negative

Question 3

What is positive predictive value and negative predictive value?

Answer 3

Positive predictive value: the probability that a patient with a positive test result actually has the disease

Negative predictive value: the probability that a patient with a negative test result actually do not have the disease

Question 4

Define incidence and prevalence.

Answer 4

Incidence: a measure of the number of new cases of a disease that develop in a population in a specified time period

Prevalence: ; the proportion of a population who have a disease in a given time period, regardless of when they first developed the characteristic.