Жизнестойкость
Petr Ya
10/5/2019
rm(list = ls())
date()## [1] "Sat Oct 5 18:44:17 2019"sessionInfo()## R version 3.6.1 (2019-07-05)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.6
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## loaded via a namespace (and not attached):
## [1] compiler_3.6.1 magrittr_1.5 tools_3.6.1 htmltools_0.3.6
## [5] yaml_2.2.0 Rcpp_1.0.2 stringi_1.4.3 rmarkdown_1.16
## [9] knitr_1.25 stringr_1.4.0 xfun_0.10 digest_0.6.21
## [13] evaluate_0.14Библиотеки
library(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, union# library(quanteda)
library(ggplot2)
#library(stringr)Загрузка таблицы
load(file = "Vitality.RData")Опистальеная статистика
summary(Vitality)## Name Sex Group Age Vovlech
## Length:46 f:35 actor:16 Min. :18.00 Min. :14.00
## Class :character m:11 dance:14 1st Qu.:19.00 1st Qu.:27.00
## Mode :character music:16 Median :20.00 Median :34.00
## Mean :20.13 Mean :33.52
## 3rd Qu.:21.00 3rd Qu.:39.75
## Max. :25.00 Max. :53.00
## Kontr Risk Vitality
## Min. :15.00 Min. : 4.00 Min. : 36.00
## 1st Qu.:22.00 1st Qu.:13.00 1st Qu.: 63.25
## Median :29.00 Median :16.00 Median : 79.50
## Mean :28.33 Mean :15.93 Mean : 77.78
## 3rd Qu.:33.75 3rd Qu.:18.75 3rd Qu.: 91.50
## Max. :46.00 Max. :27.00 Max. :115.00Сравнение групп
Вовлеченность
ggplot(Vitality, aes(Group, Vovlech)) +
geom_boxplot()
Vitality %>%
group_by(Group) %>%
summarise(n = n(), avg = mean(Vovlech), sd = sd(Vovlech))## # A tibble: 3 x 4
## Group n avg sd
## <fct> <int> <dbl> <dbl>
## 1 actor 16 36 10.7
## 2 dance 14 34.7 7.92
## 3 music 16 30 9.38summary(
aov(Vovlech ~ Group, Vitality)
)## Df Sum Sq Mean Sq F value Pr(>F)
## Group 2 317 158.31 1.769 0.183
## Residuals 43 3849 89.51kruskal.test(Vovlech ~ Group, Vitality)##
## Kruskal-Wallis rank sum test
##
## data: Vovlech by Group
## Kruskal-Wallis chi-squared = 3.3392, df = 2, p-value = 0.1883Нет значимых различий
Контроль
ggplot(Vitality, aes(Group, Kontr)) +
geom_boxplot()
Контроль
Vitality %>%
group_by(Group) %>%
summarise(n = n(), avg = mean(Kontr), sd = sd(Kontr))## # A tibble: 3 x 4
## Group n avg sd
## <fct> <int> <dbl> <dbl>
## 1 actor 16 30.5 7.97
## 2 dance 14 29 6.80
## 3 music 16 25.6 8.48summary(
aov(Kontr ~ Group, Vitality)
)## Df Sum Sq Mean Sq F value Pr(>F)
## Group 2 204.2 102.09 1.668 0.201
## Residuals 43 2631.9 61.21Нет значимых различий
kruskal.test(Kontr ~ Group, Vitality)##
## Kruskal-Wallis rank sum test
##
## data: Kontr by Group
## Kruskal-Wallis chi-squared = 3.1817, df = 2, p-value = 0.2037Риск
ggplot(Vitality, aes(Group, Risk)) +
geom_boxplot()
Риск
Vitality %>%
group_by(Group) %>%
summarise(n = n(), avg = mean(Risk), sd = sd(Risk))## # A tibble: 3 x 4
## Group n avg sd
## <fct> <int> <dbl> <dbl>
## 1 actor 16 16.9 6.02
## 2 dance 14 16.1 3.21
## 3 music 16 14.8 3.78summary(
aov(Risk ~ Group, Vitality)
)## Df Sum Sq Mean Sq F value Pr(>F)
## Group 2 34.9 17.45 0.841 0.438
## Residuals 43 891.9 20.74Нет значимых различий
kruskal.test(Risk ~ Group, Vitality)##
## Kruskal-Wallis rank sum test
##
## data: Risk by Group
## Kruskal-Wallis chi-squared = 1.3323, df = 2, p-value = 0.5137Жизнестойкость
ggplot(Vitality, aes(Group, Vitality)) +
geom_boxplot()
Vitality %>%
group_by(Group) %>%
summarise(n = n(), avg = mean(Vitality), sd = sd(Vitality))## # A tibble: 3 x 4
## Group n avg sd
## <fct> <int> <dbl> <dbl>
## 1 actor 16 83.4 23.1
## 2 dance 14 79.9 16.4
## 3 music 16 70.4 18.3summary(
aov(Vitality ~ Group, Vitality)
)## Df Sum Sq Mean Sq F value Pr(>F)
## Group 2 1439 719.3 1.874 0.166
## Residuals 43 16505 383.8Нет значимых различий