Adriel Martins
05 de Dezembro
\[ Y_{ijk} = \mu + \alpha_i + \beta_j + \alpha\beta_{ij} + \epsilon_{ijk} \] \[ \epsilon_{ijk} \sim N(0, \sigma^2) \]
| Yijk | TF | BF |
|---|---|---|
| 3.9 | SEM GIRO | V1 |
| 1.2 | SEM GIRO | V1 |
| 4.4 | SEM GIRO | V1 |
| 5.7 | SEM GIRO | V1 |
| 5.6 | SEM GIRO | V1 |
ajuste <- lm(formula = Yijk ~ TF + BF + BF:TF, model = TRUE,
contrasts = list(TF = "contr.sum", BF = "contr.sum"),
data = dt)
| TF | BF | Mean |
|---|---|---|
| GIRO | V1 | 6.183333 |
| GIRO | V2 | 9.375000 |
| SEM GIRO | V1 | 4.916667 |
| SEM GIRO | V2 | 8.500000 |
Shapiro-Wilk normality test
data: dt$eijk
W = 0.9497, p-value = 0.267
Shapiro-Wilk normality test
data: dt$eijk
W = 0.95212, p-value = 0.301
| TF | BF | Var |
|---|---|---|
| GIRO | V1 | 1.0774045 |
| GIRO | V2 | 0.6864459 |
| SEM GIRO | V1 | 0.5579011 |
| SEM GIRO | V2 | 0.5555820 |
Levene's Test for Homogeneity of Variance (center = median)
Df F value Pr(>F)
group 3 1.1542 0.3517
20
Analysis of Variance Table
Response: Yijk
Df Sum Sq Mean Sq F value Pr(>F)
TF 1 0.3172 0.3172 0.4410 0.51423
BF 1 4.3241 4.3241 6.0113 0.02353 *
TF:BF 1 0.0163 0.0163 0.0227 0.88183
Residuals 20 14.3867 0.7193
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
diff lwr upr p adj
SEM GIRO-GIRO -0.2299335 -0.9521978 0.4923308 0.5142301
diff lwr upr p adj
V2-V1 0.8489348 0.1266705 1.571199 0.02352734