Foundations of Epidemiology: Hypothesis Testing and P-Values

Flashcards covering key terms and definitions related to hypothesis testing and p-values in epidemiology.

Sensitivity

The percentage of people with the disease who test positive.

Specificity

The percentage of people without the disease who test negative.

Positive Predictive Value (PPV)

Probability that a person with a positive test result actually has the disease.

Negative Predictive Value (NPV)

Probability that a person with a negative test result is disease-free.

Internal Validity

The degree to which the study design and analysis lead to correct conclusions regarding the association.

External Validity

The extent to which study findings can be generalized to a wider population.

Type I Error (α)

The error of rejecting the null hypothesis when it is true.

Type II Error (β)

The error of failing to reject the null hypothesis when it is false.

Confidence Interval (CI)

A range of values derived from sample data that is likely to cover the true population parameter.

P-value

The probability of observing a test statistic as extreme as the one computed, given that the null hypothesis is true.

Null Hypothesis (H0)

The hypothesis stating that there is no association between exposure and disease.

Alternative Hypothesis (Ha)

The hypothesis stating that there is an association between exposure and disease.