scorpions
Brittany Aldrich
2022-11-15
Open up the CSV file
scorpions <- read.csv("newscorp.csv")Create “species” vector
species <- c(scorpions$species)Create “vegetation” vector
veg <- c(scorpions$veg_type)test
library(gmodels)## Warning: package 'gmodels' was built under R version 4.2.2with(scorpions, CrossTable(veg,species, header = FALSE))##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 250
##
##
## | species
## veg | P. silvestrii | S. gertschi | U. mordax | Row Total |
## ------------------|---------------|---------------|---------------|---------------|
## chaparral | 3 | 31 | 0 | 34 |
## | 3.738 | 5.160 | 4.624 | |
## | 0.088 | 0.912 | 0.000 | 0.136 |
## | 0.047 | 0.204 | 0.000 | |
## | 0.012 | 0.124 | 0.000 | |
## ------------------|---------------|---------------|---------------|---------------|
## grassland | 0 | 6 | 0 | 6 |
## | 1.536 | 1.516 | 0.816 | |
## | 0.000 | 1.000 | 0.000 | 0.024 |
## | 0.000 | 0.039 | 0.000 | |
## | 0.000 | 0.024 | 0.000 | |
## ------------------|---------------|---------------|---------------|---------------|
## oak woodland | 4 | 4 | 21 | 29 |
## | 1.579 | 10.539 | 73.759 | |
## | 0.138 | 0.138 | 0.724 | 0.116 |
## | 0.062 | 0.026 | 0.618 | |
## | 0.016 | 0.016 | 0.084 | |
## ------------------|---------------|---------------|---------------|---------------|
## open grassland | 0 | 1 | 0 | 1 |
## | 0.256 | 0.253 | 0.136 | |
## | 0.000 | 1.000 | 0.000 | 0.004 |
## | 0.000 | 0.007 | 0.000 | |
## | 0.000 | 0.004 | 0.000 | |
## ------------------|---------------|---------------|---------------|---------------|
## pine/oak woodland | 45 | 74 | 9 | 128 |
## | 4.566 | 0.188 | 4.061 | |
## | 0.352 | 0.578 | 0.070 | 0.512 |
## | 0.703 | 0.487 | 0.265 | |
## | 0.180 | 0.296 | 0.036 | |
## ------------------|---------------|---------------|---------------|---------------|
## riparian | 12 | 36 | 4 | 52 |
## | 0.129 | 0.608 | 1.334 | |
## | 0.231 | 0.692 | 0.077 | 0.208 |
## | 0.188 | 0.237 | 0.118 | |
## | 0.048 | 0.144 | 0.016 | |
## ------------------|---------------|---------------|---------------|---------------|
## Column Total | 64 | 152 | 34 | 250 |
## | 0.256 | 0.608 | 0.136 | |
## ------------------|---------------|---------------|---------------|---------------|
##
## Create contingency table
library(summarytools)## Warning: package 'summarytools' was built under R version 4.2.2library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniontable <- ctable(species, veg, header = FALSE)
print(table)## Cross-Tabulation, Row Proportions
## species * veg
##
## --------------- ----- ------------ ----------- -------------- ---------------- ------------------- ------------ --------------
## veg chaparral grassland oak woodland open grassland pine/oak woodland riparian Total
## species
## P. silvestrii 3 ( 4.7%) 0 (0.0%) 4 ( 6.2%) 0 (0.0%) 45 (70.3%) 12 (18.8%) 64 (100.0%)
## S. gertschi 31 (20.4%) 6 (3.9%) 4 ( 2.6%) 1 (0.7%) 74 (48.7%) 36 (23.7%) 152 (100.0%)
## U. mordax 0 ( 0.0%) 0 (0.0%) 21 (61.8%) 0 (0.0%) 9 (26.5%) 4 (11.8%) 34 (100.0%)
## Total 34 (13.6%) 6 (2.4%) 29 (11.6%) 1 (0.4%) 128 (51.2%) 52 (20.8%) 250 (100.0%)
## --------------- ----- ------------ ----------- -------------- ---------------- ------------------- ------------ --------------Create bar plot
library(ggplot2)
library(ggthemes)## Warning: package 'ggthemes' was built under R version 4.2.2ggplot(data=scorpions, aes(x=species,y=veg,fill=veg))+ geom_bar(stat="identity",color="black",position=position_dodge())+theme_stata()+scale_fill_economist()+ theme(axis.text.y = element_text(angle = 0),axis.title = element_text(face="bold"))+ labs(title="Relationship Between Species and Vegetation Type")
Run chi-square test
test <- chisq.test(table(species, veg))## Warning in chisq.test(table(species, veg)): Chi-squared approximation may be
## incorrecttest##
## Pearson's Chi-squared test
##
## data: table(species, veg)
## X-squared = 114.8, df = 10, p-value < 2.2e-16Calculate test statistic
test$statistic## X-squared
## 114.7999Calculate p-value
test$p.value## [1] 5.724566e-20library(gmodels)
with(scorpions, CrossTable(species,veg, header = FALSE))##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 250
##
##
## | veg
## species | chaparral | grassland | oak woodland | open grassland | pine/oak woodland | riparian | Row Total |
## --------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|
## P. silvestrii | 3 | 0 | 4 | 0 | 45 | 12 | 64 |
## | 3.738 | 1.536 | 1.579 | 0.256 | 4.566 | 0.129 | |
## | 0.047 | 0.000 | 0.062 | 0.000 | 0.703 | 0.188 | 0.256 |
## | 0.088 | 0.000 | 0.138 | 0.000 | 0.352 | 0.231 | |
## | 0.012 | 0.000 | 0.016 | 0.000 | 0.180 | 0.048 | |
## --------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|
## S. gertschi | 31 | 6 | 4 | 1 | 74 | 36 | 152 |
## | 5.160 | 1.516 | 10.539 | 0.253 | 0.188 | 0.608 | |
## | 0.204 | 0.039 | 0.026 | 0.007 | 0.487 | 0.237 | 0.608 |
## | 0.912 | 1.000 | 0.138 | 1.000 | 0.578 | 0.692 | |
## | 0.124 | 0.024 | 0.016 | 0.004 | 0.296 | 0.144 | |
## --------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|
## U. mordax | 0 | 0 | 21 | 0 | 9 | 4 | 34 |
## | 4.624 | 0.816 | 73.759 | 0.136 | 4.061 | 1.334 | |
## | 0.000 | 0.000 | 0.618 | 0.000 | 0.265 | 0.118 | 0.136 |
## | 0.000 | 0.000 | 0.724 | 0.000 | 0.070 | 0.077 | |
## | 0.000 | 0.000 | 0.084 | 0.000 | 0.036 | 0.016 | |
## --------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|
## Column Total | 34 | 6 | 29 | 1 | 128 | 52 | 250 |
## | 0.136 | 0.024 | 0.116 | 0.004 | 0.512 | 0.208 | |
## --------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|-------------------|
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