Project measure / variable:   Bodnar1   chow9

ID, description, units MPD:22604   chow9   daily chow intake with sucrose in drinking water   [g]  20% 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 20% sucrose



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested11 strains
Mean of the strain means3.05   g
Median of the strain means2.97   g
SD of the strain means± 1.04
Coefficient of variation (CV)0.341
Min–max range of strain means1.42   –   4.42   g
Mean sample size per strain9.9   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 10 110.2706 11.0271 6.7024 < 0.0001
Residuals 107 176.0396 1.6452


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 2.83 1.78   10 0.564 0.63 -0.21
AKR/J m 4.42 0.976   10 0.309 0.221 3.1, 6.0 1.32
BALB/cJ m 4.14 0.853   10 0.27 0.206 2.9, 5.7 1.05
C3H/HeJ m 3.63 1.02   10 0.323 0.281 2.0, 5.7 0.56
C57BL/10J m 1.42 0.835   10 0.264 0.588 0.1, 3.2 -1.57
C57BL/6J m 2.97 0.939   10 0.297 0.316 1.9, 5.0 -0.07
CBA/J m 2.43 0.731   9 0.244 0.301 1.4, 3.5 -0.59
Crl:CD-1(ICR) m 3.82 2.19   20 0.489 0.573 1.2, 10.8 0.74
DBA/2J m 3.96 0.891   10 0.282 0.225 2.6, 5.9 0.88
SJL/J m 1.48 0.608   9 0.203 0.411 0.3, 2.6 -1.51
SWR/J m 2.41 0.615   10 0.195 0.255 1.3, 3.4 -0.61


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
A/J m 2.83 0.4056 3.6341 2.0259
AKR/J m 4.42 0.4056 5.2241 3.6159
BALB/cJ m 4.14 0.4056 4.9441 3.3359
C3H/HeJ m 3.63 0.4056 4.4341 2.8259
C57BL/10J m 1.42 0.4056 2.2241 0.6159
C57BL/6J m 2.97 0.4056 3.7741 2.1659
CBA/J m 2.4333 0.4276 3.2809 1.5858
Crl:CD-1(ICR) m 3.82 0.2868 4.3886 3.2514
DBA/2J m 3.96 0.4056 4.7641 3.1559
SJL/J m 1.4778 0.4276 2.3254 0.6302
SWR/J m 2.41 0.4056 3.2141 1.6059




  GWAS USING LINEAR MIXED MODELS