library(readr)
library(dplyr)
library(ggplot2)
library(knitr)
library(kableExtra)
library(sjlabelled)
library(sjmisc)
library(sjstats)
library(ggeffects)
library(sjPlot)
library(psych)
library(tidyverse)
library(magrittr)
library(car)
library(cowplot)
library(gridExtra)
library(snakecase)
library(car)
library(stargazer)
library(scales)
pokemons = read_csv("pokemon.csv")
task1 = pokemons %>%
select(is_legendary, generation)
summary(task1)
## is_legendary generation
## Min. :0.00000 Min. :1.00
## 1st Qu.:0.00000 1st Qu.:2.00
## Median :0.00000 Median :4.00
## Mean :0.08739 Mean :3.69
## 3rd Qu.:0.00000 3rd Qu.:5.00
## Max. :1.00000 Max. :7.00
task1$is_legendary = as.factor(task1$is_legendary)
task1$generation = as.factor(task1$generation)
task1 = task1 %>%
filter(is_legendary == 1) %>%
group_by(generation)
summary(task1)
## is_legendary generation
## 0: 0 1: 5
## 1:70 2: 6
## 3:10
## 4:13
## 5:13
## 6: 6
## 7:17
task2 = pokemons %>%
select(sp_attack, sp_defense, speed, weight_kg)
summary(task2)
## sp_attack sp_defense speed weight_kg
## Min. : 10.00 Min. : 20.00 Min. : 5.00 Min. : 0.10
## 1st Qu.: 45.00 1st Qu.: 50.00 1st Qu.: 45.00 1st Qu.: 9.00
## Median : 65.00 Median : 66.00 Median : 65.00 Median : 27.30
## Mean : 71.31 Mean : 70.91 Mean : 66.33 Mean : 61.38
## 3rd Qu.: 91.00 3rd Qu.: 90.00 3rd Qu.: 85.00 3rd Qu.: 64.80
## Max. :194.00 Max. :230.00 Max. :180.00 Max. :999.90
## NA's :20
task2 <- task2[!is.na(task2$weight_kg),]
task2$sp_attack = as.numeric(as.character(task2$sp_attack))
task2$sp_defense = as.numeric(as.character(task2$sp_defense))
task2$speed = as.numeric(as.character(task2$speed))
task2$weight_kg = as.numeric(as.character(task2$weight_kg))
cor(task2)
## sp_attack sp_defense speed weight_kg
## sp_attack 1.0000000 0.5048682 0.44534428 0.24521797
## sp_defense 0.5048682 1.0000000 0.22357290 0.30652308
## speed 0.4453443 0.2235729 1.00000000 0.05138394
## weight_kg 0.2452180 0.3065231 0.05138394 1.00000000
sjp.corr(task2, show.legend = TRUE)
task3 = pokemons %>%
select(speed, type1)
task3 <- task3[!is.na(task3$speed),]
summary(task3)
## speed type1
## Min. : 5.00 Length:801
## 1st Qu.: 45.00 Class :character
## Median : 65.00 Mode :character
## Mean : 66.33
## 3rd Qu.: 85.00
## Max. :180.00
task3$type1 = as.factor(task3$type1)
ggplot() + geom_boxplot(data = task3, aes(x = type1, y = speed)) + coord_flip()
oneway.test(task3$speed ~ task3$type1, var.equal = T)
##
## One-way analysis of means
##
## data: task3$speed and task3$type1
## F = 3.5553, num df = 17, denom df = 783, p-value = 1.672e-06
aov.out <- aov(task3$speed ~ task3$type1)
summary(aov.out)
## Df Sum Sq Mean Sq F value Pr(>F)
## task3$type1 17 47906 2818.0 3.555 1.67e-06 ***
## Residuals 783 620616 792.6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
par(mar = c(5, 15, 3, 1))
Tukey <- TukeyHSD(aov.out)
plot(Tukey, las = 2, col = "red" )
Tukey
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = task3$speed ~ task3$type1)
##
## $`task3$type1`
## diff lwr upr p adj
## dark-bug 11.74090038 -9.934098 33.415899 0.9127770
## dragon-bug 12.54166667 -9.698247 34.781581 0.8808551
## electric-bug 21.84081197 2.246655 41.434969 0.0124578
## fairy-bug -9.90277778 -35.873402 16.067847 0.9974961
## fighting-bug 0.71626984 -21.232914 22.665454 1.0000000
## fire-bug 9.77670940 -8.158504 27.711923 0.9082681
## flying-bug 36.09722222 -21.974859 94.169304 0.7691356
## ghost-bug -5.23611111 -27.476025 17.003803 0.9999965
## grass-bug -4.54380342 -20.650101 11.562494 0.9999515
## ground-bug -3.60069444 -24.538881 17.337492 1.0000000
## ice-bug -0.83031401 -24.434839 22.774211 1.0000000
## normal-bug 5.96388889 -9.115696 21.043473 0.9961502
## poison-bug 0.61805556 -20.320131 21.556242 1.0000000
## psychic-bug 11.58149895 -6.255199 29.418197 0.7028121
## rock-bug -6.14722222 -24.874906 12.580461 0.9996185
## steel-bug -6.98611111 -30.214944 16.242721 0.9998820
## water-bug 0.35160819 -14.483866 15.187082 1.0000000
## dragon-dark 0.80076628 -25.555068 27.156601 1.0000000
## electric-dark 10.09991158 -14.065088 34.264911 0.9927961
## fairy-dark -21.64367816 -51.215448 7.928091 0.4834427
## fighting-dark -11.02463054 -37.135603 15.086342 0.9919431
## fire-dark -1.96419098 -24.804684 20.876302 1.0000000
## flying-dark 24.35632184 -35.413092 84.125736 0.9945749
## ghost-dark -16.97701149 -43.332846 9.378823 0.7156480
## grass-dark -16.28470380 -37.719000 5.149592 0.4109502
## ground-dark -15.34159483 -40.608646 9.925457 0.8007264
## ice-dark -12.57121439 -40.088297 14.945868 0.9814886
## normal-dark -5.77701149 -26.450910 14.896887 0.9999576
## poison-dark -11.12284483 -36.389896 14.144207 0.9873816
## psychic-dark -0.15940143 -22.922618 22.603815 1.0000000
## rock-dark -17.88812261 -41.356023 5.579778 0.4046695
## steel-dark -18.72701149 -45.922505 8.468482 0.6000999
## water-dark -11.38929220 -31.885817 9.107233 0.8934512
## electric-dragon 9.29914530 -15.373824 33.972115 0.9978221
## fairy-dragon -22.44444444 -52.432738 7.543850 0.4399475
## fighting-dragon -11.82539683 -38.407178 14.756385 0.9859111
## fire-dragon -2.76495726 -26.142218 20.612304 1.0000000
## flying-dragon 23.55555556 -36.421032 83.532143 0.9964503
## ghost-dragon -17.77777778 -44.600123 9.044568 0.6684113
## grass-dragon -17.08547009 -39.090862 4.919922 0.3696336
## ground-dragon -16.14236111 -41.895654 9.610932 0.7571817
## ice-dragon -13.37198068 -41.336209 14.592248 0.9709684
## normal-dragon -6.57777778 -27.843203 14.687647 0.9998271
## poison-dragon -11.92361111 -37.676904 13.829682 0.9788303
## psychic-dragon -0.96016771 -24.261932 22.341597 1.0000000
## rock-dragon -18.68888889 -42.679524 5.301746 0.3633989
## steel-dragon -19.52777778 -47.175619 8.120063 0.5523110
## water-dragon -12.19005848 -33.283084 8.902967 0.8574912
## fairy-electric -31.74358974 -59.825879 -3.661300 0.0101273
## fighting-electric -21.12454212 -45.535775 3.286691 0.1888464
## fire-electric -12.06410256 -32.940250 8.812045 0.8575433
## flying-electric 14.25641026 -44.790252 73.303072 0.9999949
## ghost-electric -27.07692308 -51.749892 -2.403954 0.0155631
## grass-electric -26.38461538 -45.712172 -7.057058 0.0003012
## ground-electric -25.44150641 -48.947874 -1.935139 0.0188444
## ice-electric -22.67112598 -48.580878 3.238626 0.1737773
## normal-electric -15.87692308 -34.357602 2.603756 0.1991003
## poison-electric -21.22275641 -44.729124 2.283611 0.1352016
## psychic-electric -10.25931301 -31.050884 10.532258 0.9609914
## rock-electric -27.98803419 -49.548827 -6.427242 0.0008871
## steel-electric -28.82692308 -54.394878 -3.258968 0.0105268
## water-electric -21.48920378 -39.771242 -3.207165 0.0054784
## fighting-fairy 10.61904762 -19.154274 40.392369 0.9988937
## fire-fairy 19.67948718 -7.271503 46.630478 0.4879937
## flying-fairy 46.00000000 -15.457714 107.457714 0.4398388
## ghost-fairy 4.66666667 -25.321627 34.654961 1.0000000
## grass-fairy 5.35897436 -20.411102 31.129050 0.9999995
## ground-fairy 6.30208333 -22.733957 35.338124 0.9999990
## ice-fairy 9.07246377 -21.941366 40.086293 0.9999195
## normal-fairy 15.86666667 -9.274492 41.007825 0.7471384
## poison-fairy 10.52083333 -18.515207 39.556874 0.9986537
## psychic-fairy 21.48427673 -5.401255 48.369808 0.3167357
## rock-fairy 3.75555556 -23.729170 31.240281 1.0000000
## steel-fairy 2.91666667 -27.812190 33.645524 1.0000000
## water-fairy 10.25438596 -14.741120 35.249891 0.9941478
## fire-fighting 9.06043956 -14.040410 32.161289 0.9965062
## flying-fighting 35.38095238 -24.488439 95.250343 0.8334572
## ghost-fighting -5.95238095 -32.534162 20.629401 0.9999983
## grass-fighting -5.26007326 -26.971594 16.451448 0.9999946
## ground-fighting -4.31696429 -29.819611 21.185683 1.0000000
## ice-fighting -1.54658385 -29.280155 26.186987 1.0000000
## normal-fighting 5.24761905 -15.713564 26.208802 0.9999913
## poison-fighting -0.09821429 -25.600861 25.404433 1.0000000
## psychic-fighting 10.86522911 -12.159217 33.889675 0.9744544
## rock-fighting -6.86349206 -30.584864 16.857879 0.9999309
## steel-fighting -7.70238095 -35.116903 19.712141 0.9999542
## water-fighting -0.36466165 -21.150922 20.421599 1.0000000
## flying-fire 26.32051282 -32.196572 84.837598 0.9842099
## ghost-fire -15.01282051 -38.390082 8.364441 0.7204420
## grass-fire -14.32051282 -31.964078 3.323052 0.2893215
## ground-fire -13.37740385 -35.519902 8.765094 0.8070720
## ice-fire -10.60702341 -35.286087 14.072040 0.9902234
## normal-fire -3.81282051 -20.524386 12.898745 0.9999978
## poison-fire -9.15865385 -31.301152 12.983844 0.9935846
## psychic-fire 1.80478955 -17.431384 21.040963 1.0000000
## rock-fire -15.92393162 -35.989043 4.141180 0.3291539
## steel-fire -16.76282051 -41.082796 7.557155 0.5983406
## water-fire -9.42510121 -25.916731 7.066529 0.8685085
## ghost-flying -41.33333333 -101.309921 18.643255 0.5986192
## grass-flying -40.64102564 -98.623697 17.341645 0.5668859
## ground-flying -39.69791667 -99.204093 19.808259 0.6571568
## ice-flying -36.92753623 -97.423412 23.568339 0.7938291
## normal-flying -30.13333333 -87.839236 27.572569 0.9355629
## poison-flying -35.47916667 -94.985343 24.027009 0.8231807
## psychic-flying -24.51572327 -83.002689 33.971242 0.9925622
## rock-flying -42.24444444 -101.009259 16.520370 0.5183565
## steel-flying -43.08333333 -103.433611 17.266944 0.5318048
## water-flying -35.74561404 -93.388208 21.896980 0.7724532
## grass-ghost 0.69230769 -21.313084 22.697699 1.0000000
## ground-ghost 1.63541667 -24.117876 27.388710 1.0000000
## ice-ghost 4.40579710 -23.558431 32.370025 1.0000000
## normal-ghost 11.20000000 -10.065425 32.465425 0.9307322
## poison-ghost 5.85416667 -19.899126 31.607460 0.9999979
## psychic-ghost 16.81761006 -6.484155 40.119375 0.5106646
## rock-ghost -0.91111111 -24.901746 23.079524 1.0000000
## steel-ghost -1.75000000 -29.397841 25.897841 1.0000000
## water-ghost 5.58771930 -15.505307 26.680745 0.9999802
## ground-grass 0.94310897 -19.745805 21.632023 1.0000000
## ice-grass 3.71348941 -19.670204 27.097183 1.0000000
## normal-grass 10.50769231 -4.223817 25.239201 0.5334465
## poison-grass 5.16185897 -15.527055 25.850773 0.9999917
## psychic-grass 16.12530237 -1.418109 33.668714 0.1158630
## rock-grass -1.60341880 -20.051986 16.845148 1.0000000
## steel-grass -2.44230769 -25.446702 20.562086 1.0000000
## water-grass 4.89541161 -9.586121 19.376944 0.9994404
## ice-ground 2.77038043 -24.170146 29.710907 1.0000000
## normal-ground 9.56458333 -10.335472 29.464639 0.9695145
## poison-ground 4.21875000 -20.419148 28.856648 1.0000000
## psychic-ground 15.18219340 -6.880584 37.244970 0.6013661
## rock-ground -2.54652778 -25.335658 20.242603 1.0000000
## steel-ground -3.38541667 -29.997388 23.226554 1.0000000
## water-ground 3.95230263 -15.763418 23.668023 0.9999997
## normal-ice 6.79420290 -15.894520 29.482926 0.9998888
## poison-ice 1.44836957 -25.492157 28.388896 1.0000000
## psychic-ice 12.41181296 -12.195749 37.019375 0.9523844
## rock-ice -5.31690821 -30.577756 19.943939 0.9999994
## steel-ice -6.15579710 -34.912761 22.601166 0.9999992
## water-ice 1.18192220 -21.345297 23.709141 1.0000000
## poison-normal -5.34583333 -25.245889 14.554222 0.9999758
## psychic-normal 5.61761006 -10.988182 22.223402 0.9994351
## rock-normal -12.11111111 -29.670458 5.448236 0.5970948
## steel-normal -12.95000000 -35.247605 9.347605 0.8524052
## water-normal -5.61228070 -18.942541 7.717979 0.9921919
## psychic-poison 10.96344340 -11.099334 33.026220 0.9583906
## rock-poison -6.76527778 -29.554408 16.023853 0.9999014
## steel-poison -7.60416667 -34.216138 19.007804 0.9999420
## water-poison -0.26644737 -19.982168 19.449273 1.0000000
## rock-psychic -17.72872117 -37.705823 2.248381 0.1556390
## steel-psychic -18.56761006 -42.815025 5.679805 0.3958533
## water-psychic -11.22989076 -27.614327 5.154546 0.6087110
## steel-rock -0.83888889 -25.749037 24.071259 1.0000000
## water-rock 6.49883041 -10.851331 23.848992 0.9979790
## water-steel 7.33771930 -14.795528 29.470966 0.9995654
# посмотреть на те, которые значимые
# найти ту категорию, у которой наибольшая разница со всеми остальными!
task4 = pokemons %>%
select(is_legendary, sp_attack)
task4$is_legendary = as.factor(task4$is_legendary)
summary(task4)
## is_legendary sp_attack
## 0:731 Min. : 10.00
## 1: 70 1st Qu.: 45.00
## Median : 65.00
## Mean : 71.31
## 3rd Qu.: 91.00
## Max. :194.00
task4$attack = ifelse(task4$is_legendary == 1, "legend", "not_legend")
ggplot() + geom_boxplot(data = task4, aes(x = attack, sp_attack))
t.test(task4$sp_attack ~ task4$attack)
##
## Welch Two Sample t-test
##
## data: task4$sp_attack by task4$attack
## t = 10.944, df = 78.733, p-value < 2.2e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 38.05573 54.97703
## sample estimates:
## mean in group legend mean in group not_legend
## 113.75714 67.24077
task5 = pokemons %>%
select(hp, sp_defense, sp_attack, is_legendary)
task5$is_legendary = as.factor(task5$is_legendary)
task5$legend = ifelse(task5$is_legendary == 1, "legend", "not_legend")
model1 = lm(hp ~ sp_defense + sp_attack + legend, data = task5)
tab_model(model1)
|
|
hp
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
56.62
|
47.23 – 66.01
|
<0.001
|
|
sp defense
|
0.20
|
0.13 – 0.27
|
<0.001
|
|
sp attack
|
0.16
|
0.10 – 0.22
|
<0.001
|
|
legendnot_legend
|
-14.71
|
-21.21 – -8.22
|
<0.001
|
|
Observations
|
801
|
|
R2 / R2 adjusted
|
0.198 / 0.195
|
model2 = lm(hp ~ sp_defense + sp_attack + legend + sp_defense*legend, data = task5)
tab_model(model2)
|
|
hp
|
|
Predictors
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
84.33
|
63.24 – 105.42
|
<0.001
|
|
sp defense
|
-0.06
|
-0.25 – 0.13
|
0.557
|
|
sp attack
|
0.15
|
0.09 – 0.21
|
<0.001
|
|
legendnot_legend
|
-44.28
|
-65.48 – -23.09
|
<0.001
|
|
sp_defense:legendnot_legend
|
0.30
|
0.09 – 0.50
|
0.004
|
|
Observations
|
801
|
|
R2 / R2 adjusted
|
0.206 / 0.202
|
plot_model(model2, type = "int", terms = "legend", mdrt.values = "minmax")
#For legend pokemons the relationship between defence and hp is not significant (because p>0.05 in defense variable itself). However, if the referent group is not legend pokemons, the higher sp_defense means the higher hit point