Type I error – rejects null hypothesis incorrectly → falsely assumed there was a ­difference when no difference exists

  Type II error – accepts null hypothesis incorrectly because of small sample size → the treatments are interpreted as equal when there is actually a difference

  Null hypothesis – hypothesis that no difference exists between groups

  p < 0.05 rejects the null hypothesis

•  p < 0.05 = > 95% likelihood that the difference between the populations is true

•  < 5% likelihood that the difference is not true and occurred by chance alone

  Variance – spread of data around a mean

  Parameter – population

  Numeric terms – example: 2, 7, 7, 8, 9, 11, 15

•  Mode – most frequently occurring value = 7

•  Mean – average = 9

•  Median – middle value of a set of data (50th percentile) = 8

TRIALS AND STUDIES

  Randomized controlled trial – prospective study with random assignment to treatment and nontreatment groups

•  Avoids treatment biases

  Double-blind controlled trial – prospective study in which patient and doctor are blind to the treatment

•  Avoids observational biases

  Cohort study – prospective study → compares disease rate between exposed and unexposed groups (nonrandom assignment)

  Case-control study – retrospective study in which those who have the disease are compared with a similar population who do not have the disease; the frequency of the suspected risk factor is then compared between the 2 groups

  Meta-analysis – combining data from different studies

QUANTITATIVE VARIABLES

  Student’s t test – 2 independent groups and variable is quantitative → compares means (mean weight between 2 groups)

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