# Statistics with R, part 2

### From BioDivBorneo2010

## Data types

- Independent
- Measurements
- Factors

- Dependent
- Measurements
- Counts (in different classes)
- Species Composition

## Statistical tests

A simple classification of tests, based on input data class:

independent variable: | Continuous | Nominal(Y/N, live/die..., or Categorical) |

dependent variable: | ||

Continuous (measurement) | scatterplots, cor.test, lm, glm | box plots, t.tests, wilcox.test, lm, glm |

Continuous (counts) | glm(..., family=poisson) | glm(..., family=poisson), wilcox.test |

Nominal or categorical | logistic regression (glm, family=binomial) | contingency tables, chisq.test, fisher.test |

x <- c(1,2,3,4,4,5,6,8,9,10) y <- c(2,3,4,4,5,6,8,8,9,11) plot(y~x) cor.test(x,y) wilcox.test(x,y) summary( lm(y ~ x) ) xy.lm <- lm(y ~ x) xy.lm abline(xy.lm) bird <- c("b","g","g","g","g","b","b","b","b","b") build <- c("r","w","r","r","r","w","w","w","w","w") table(bird,build) chisq.test(bird, build) bird2 <- c(bird,bird) build2 <- c(build,build) table(bird2,build2) chisq.test(bird2, build2)