Herinner het model met enkel dosis-effect uit het practicum enkelvoudige lineaire regressie, hier enkel voor de goudvissen:
\[y_i=\beta_0+\beta_d x_d + \epsilon_i,\]lm1 <- lm(log2minsurv~dosis,
data = poison %>%
filter(soort == 1)) # Filter op goudvissen
summary(lm1)
# Call:
# lm(formula = log2minsurv ~ dosis, data = poison %>% filter(soort ==
# 1))
# Residuals:
# Min 1Q Median 3Q Max
# -1.38188 -0.40662 -0.01251 0.39992 0.89113
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 3.9188 0.4520 8.670 2.43e-10 ***
# dosis -0.9006 0.2796 -3.221 0.00271 **
# ---
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# Residual standard error: 0.5557 on 36 degrees of freedom
# Multiple R-squared: 0.2238, Adjusted R-squared: 0.2022
# F-statistic: 10.38 on 1 and 36 DF, p-value: 0.002707