1. Extreme Deviations Herds with large percentage of their cows on Elite List may have two management systems in their herds: High producers Low producers Can cause inflated evaluations when high & low producers are in the same management group

2. Herds with Elite Cows ~300 herds with 5+ cows on elite list Do their descriptive and normality statistics provide any useful characteristics to identify potentially “bimodal” herds? Does their 1 st lactation ME milk deviation distribution look “visually suspicious”?

3. Look suspicious to you?

4. Data 12 most “important” dairy states Calculate each cow’s 1 st lactation ME milk deviation from herd annual mean ME milk 1997-2001 18194 herds N  10 (per year) Descriptive statistics, Normality test statistics Sub data sets of herds with 5+ cows on elite list

5. Statistics (1) Descriptive statistics: Skewness (SKEW) Kurtosis (KUR) Standard error of the mean (STDMEAN) Standard deviation /  Sum of weights

6. Statistics (2) Normality statistics: Normal vs. non-normal Kolmogorov statistic (KS) Problems with normality tests: Very sensitive to herd size (i.e. >30% of CA herds are “not normally” distributed compared to < 3% in PA, WI, MN) Should not be used as only criteria

7. Preliminary Results Herds with +5 cows on elite list, “not normal”, “visually suspicious”, had higher SKEW and STDMEAN than herds that “looked okay” Herds with +5 cows on elite list, “not-normal”, had higher SKEW, KUR, and KS than herds designated “normal” All herds, “not-normal”, had higher SKEW and KUR than herds designated “normal”

8. Identifying Herds Use normality and descriptive statistics: KS  0.08 & (KUR  0.8 || SKEW  0.35) & STDMEAN  250 This threshold successfully identifies ALL of the “visually suspicious” herds and ~29% of all herds (5387 out of 18194) If threshold restricted to herds found not normally distributed first (880 out of 18194), it identifies only 235 herds

9. STDMEAN & KS vs. % on Elite List The higher STDMEAN or KS, the larger the % of cows on the Elite List

10. Adjusting Herd Data Based on the value of KS and STDMEAN, incrementally adjust heritability (as in heterogeneous variance adjustment) Result: records from herds with abnormal distributions receive less weight