Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: sum.fw$fw ~ sum.fw$Treatment + (1 | as.factor(sum.fw$Expt_no))

REML criterion at convergence: 30.1

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-0.92278 -0.59220  0.00971  0.56936  0.91600 

Random effects:
 Groups                    Name        Variance Std.Dev.
 as.factor(sum.fw$Expt_no) (Intercept) 4.90138  2.2139  
 Residual                              0.06929  0.2632  
Number of obs: 12, groups:  as.factor(sum.fw$Expt_no), 6

Fixed effects:
                         Estimate Std. Error     df t value Pr(>|t|)    
(Intercept)                6.4542     0.9102 5.0702   7.091 0.000815 ***
sum.fw$TreatmentFeedback   0.8682     0.1520 5.0000   5.713 0.002297 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
sm.fw$TrtmF -0.083
