Biostats: Measures of Central Tendency, Standard Deviation, Bias, Chance, Hypothesis Testing, Estimation, P-value, Type I and Type II Error, Confidence Intervals, Statistical Significance, Clinical Importance

Mean

Arithmetic average of a data set

Median

Middle value of a data set when ordered

Mode

Most frequently occurring value in a data set

Standard Deviation

Measure of variation in a set of values

Bias

Systematic error that deviates from the truth

Chance

Random variation in data, not due to relationship

Hypothesis Testing

Deciding if there's enough evidence to reject null hypothesis

Estimation

Inferring population parameter based on sample data

P-value

Strength of evidence against null hypothesis

Type I Error

Incorrectly rejecting null hypothesis

Type II Error

Incorrectly failing to reject null hypothesis

Confidence Intervals

Range of values believed to contain true population parameter

Statistical Significance

Relationship not due to chance, indicated by p-value

Clinical Importance

Magnitude of effect in real-world or clinical setting

Cohort Study

Observational study tracking a group over time

Cross-sectional Study

Observational study at a single point in time

Prospective Cohort Study

Cohort study following participants forward in time

Retrospective Cohort Study

Cohort study using historical data

Confounding

Factors that distort the relationship between exposure and outcome

Effect Modification

When the effect of an exposure differs based on another factor

Absolute Risk

Risk of an event occurring in a population

Relative Risk

Ratio of the risk in exposed group to unexposed group

Null Hypothesis

Statement of no effect or difference

Alternative Hypothesis

Statement of some effect or difference

Point Estimate

Single value estimate of a population parameter

Interval Estimate

Range of values within which the parameter is estimated to lie