One way Anova
## Analysis of Variance Table
##
## Response: Bee.diversity
## Df Sum Sq Mean Sq F value Pr(>F)
## Setting 2 106.921 53.460 182.74 < 2.2e-16 ***
## Residuals 49 14.335 0.293
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = d$Bee.diversity ~ d$Setting)
##
## $`d$Setting`
## diff lwr upr p adj
## Semi-rural-Rural -1.618056 -2.124358 -1.111753 0
## Urban-Rural -3.344444 -3.771396 -2.917493 0
## Urban-Semi-rural -1.726389 -2.185486 -1.267292 0
## Analysis of Variance Table
##
## Response: Butterfly.diversity
## Df Sum Sq Mean Sq F value Pr(>F)
## Setting 2 331.13 165.565 231.65 < 2.2e-16 ***
## Residuals 49 35.02 0.715
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = d$Butterfly.diversity ~ d$Setting)
##
## $`d$Setting`
## diff lwr upr p adj
## Semi-rural-Rural -3.486111 -4.277470 -2.694752 0
## Urban-Rural -5.938889 -6.606221 -5.271557 0
## Urban-Semi-rural -2.452778 -3.170354 -1.735202 0
Regression
##
## Call:
## lm(formula = Butterfly.diversity ~ Bee.diversity, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2001 -0.6716 -0.1235 0.5945 4.4315
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.1236 0.4221 -0.293 0.771
## Bee.diversity 1.5751 0.1038 15.175 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.143 on 50 degrees of freedom
## Multiple R-squared: 0.8216, Adjusted R-squared: 0.818
## F-statistic: 230.3 on 1 and 50 DF, p-value: < 2.2e-16