Project measure / variable:   Bodnar1   chow3

ID, description, units MPD:22602   chow3   daily chow intake with sucrose in drinking water   [g]  0.01% sucrose  
sucrose study
Data set, strains Bodnar1   inbred   11 strains     sex: m     age: 13-17wks
Procedure intake monitoring
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  STRAIN COMPARISON PLOT
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Bodnar1 - daily chow intake with sucrose in drinking water 0.01% sucrose



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested11 strains
Mean of the strain means4.55   g
Median of the strain means4.33   g
SD of the strain means± 1.00
Coefficient of variation (CV)0.221
Min–max range of strain means3.17   –   6.67   g
Mean sample size per strain10.0   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 10 102.1617 10.2162 8.7384 < 0.0001
Residuals 108 126.264 1.1691


Q-Q normality assessment based on residuals

  


  STRAIN MEANS (UNADJUSTED)
  
Select table page:
Strain Sex Mean SD N mice SEM CV Min, Max Z score
A/J m 4.03 1.53   10 0.482 0.379 -0.52
AKR/J m 4.44 0.582   10 0.184 0.131 3.4, 5.1 -0.11
BALB/cJ m 6.67 0.921   10 0.291 0.138 4.7, 7.9 2.11
C3H/HeJ m 5.21 0.569   10 0.18 0.109 4.5, 6.4 0.65
C57BL/10J m 3.69 0.952   10 0.301 0.258 2.1, 6.0 -0.86
C57BL/6J m 4.33 0.783   10 0.248 0.181 3.1, 5.4 -0.22
CBA/J m 3.75 0.602   10 0.19 0.161 3.0, 4.7 -0.8
Crl:CD-1(ICR) m 5.15 1.84   20 0.412 0.358 1.8, 8.1 0.59
DBA/2J m 5.54 0.703   10 0.222 0.127 4.1, 6.3 0.98
SJL/J m 3.17 0.477   9 0.159 0.151 2.6, 3.8 -1.38
SWR/J m 4.1 0.668   10 0.211 0.163 3.1, 4.9 -0.45


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
A/J m 4.03 0.3419 4.7078 3.3522
AKR/J m 4.44 0.3419 5.1178 3.7622
BALB/cJ m 6.67 0.3419 7.3478 5.9922
C3H/HeJ m 5.21 0.3419 5.8878 4.5322
C57BL/10J m 3.69 0.3419 4.3678 3.0122
C57BL/6J m 4.33 0.3419 5.0078 3.6522
CBA/J m 3.75 0.3419 4.4278 3.0722
Crl:CD-1(ICR) m 5.15 0.2418 5.6292 4.6708
DBA/2J m 5.54 0.3419 6.2178 4.8622
SJL/J m 3.1667 0.3604 3.8811 2.4523
SWR/J m 4.1 0.3419 4.7778 3.4222




  GWAS USING LINEAR MIXED MODELS