Quantitative Association Rules Based on Statistical Inference Theory [Aumann and LindelIODMKD'o3] Finding extraordinary and therefore interesting phenomena, e. g (Sex female)=> Wage: mean =$ /hr(overall mean =$9) LHS: a subset of the population RHS: an extraordinary behavior of this subset The rule is accepted only if a statistical test(e. g. Z-test)confirms the inference with high confidence Subrule: highlights the extraordinary behavior of a subset of the pop of the super rule E.g. ,(Sex female)( South yes)=> mean wage= $6.3/hr Two forms of rules Categorical = quantitative rules or Quantitative = quantitative rules E.g. Education in [14-18](yrs)=> mean wage = $11.64/hr Open problem Efficient methods for LHS containing two or more quantitative attributes12 Quantitative Association Rules Based on Statistical Inference Theory [Aumann and Lindell@DMKD’03] ◼ Finding extraordinary and therefore interesting phenomena, e.g., (Sex = female) => Wage: mean=$7/hr (overall mean = $9) ◼ LHS: a subset of the population ◼ RHS: an extraordinary behavior of this subset ◼ The rule is accepted only if a statistical test (e.g., Z-test) confirms the inference with high confidence ◼ Subrule: highlights the extraordinary behavior of a subset of the pop. of the super rule ◼ E.g., (Sex = female) ^ (South = yes) => mean wage = $6.3/hr ◼ Two forms of rules ◼ Categorical => quantitative rules, or Quantitative => quantitative rules ◼ E.g., Education in [14-18] (yrs) => mean wage = $11.64/hr ◼ Open problem: Efficient methods for LHS containing two or more quantitative attributes