model = 
Linear regression model:
    freq ~ 1 + genotype*state

Estimated Coefficients:
                                 <strong>Estimate</strong>      <strong>SE</strong>       <strong>tStat</strong>       <strong>pValue</strong>  
                                 <strong>________</strong>    <strong>______</strong>    <strong>_______</strong>    <strong>__________</strong>
    <strong>(Intercept)              </strong>     10.348     1.0659      9.708     1.363e-11
    <strong>genotype_WT              </strong>    -3.7141     1.5074    -2.4639      0.018656
    <strong>state_is rem             </strong>    -8.0136     1.5074    -5.3161    5.7021e-06
    <strong>state_nrem is            </strong>     6.4562     1.5074     4.2829    0.00013099
    <strong>genotype_WT:state_is rem </strong>     3.8346     2.1318     1.7987      0.080452
    <strong>genotype_WT:state_nrem is</strong>    0.40343     2.1318    0.18924       0.85097

Number of observations: 42, Error degrees of freedom: 36
Root Mean Squared Error: 2.82
R-squared: 0.811,  Adjusted R-Squared: 0.784
F-statistic vs. constant model: 30.8, p-value = 4.6e-12