2024-11-28_ННГУ_pr
ВерловНА
2024-11-28
ТОчечные оценки
x <- 1:100
y <- rnorm(x, mean = 50, sd = 10)
plot(x, y)
hist(y)
оценка - средняя
x <- 1:100
y <- rnorm(x, mean = 50, sd = 10)
mean(y)## [1] 49.70675sd(y)## [1] 9.827458our_sd <- sqrt(sum((y - mean(y))^2)/(length(y)-1))
our_sd## [1] 9.827458Интервальные оценки
для нормального распределения
sample <- replicate(500, mean(rnorm(100, mean = 30, sd = 3)))
p1 <- hist(rnorm(100, mean = 30, sd = 3))
p2 <- hist(sample)
plot(p1, col = "red")
plot(p2, col="blue", add = T)
sample_sample <- rnorm(100, mean = 30, sd = 3)
sd(rnorm(100, mean = 30, sd = 3))## [1] 3.024488sd(sample)## [1] 0.3009721se <- sd(sample_sample)/sqrt(length(sample_sample))
se## [1] 0.3299886для (не)нормального распределения
log_sample <- rlnorm(10000)
hist(log_sample, breaks = 200)
log_mean_sample <- replicate(1000, mean(rlnorm(10000)))
p1 <- hist(log_sample, breaks = 200)
p2 <- hist(log_mean_sample)
plot(p1, col = "red", xlim = c(0, 4), ylim = c(0, 100))
plot(p2, col="blue", add = T)
ggplot2
бобры
library(tidyverse)## Warning: пакет 'tidyverse' был собран под R версии 4.2.3## Warning: пакет 'ggplot2' был собран под R версии 4.2.3## Warning: пакет 'tibble' был собран под R версии 4.2.3## Warning: пакет 'readr' был собран под R версии 4.2.3## Warning: пакет 'purrr' был собран под R версии 4.2.3## Warning: пакет 'dplyr' был собран под R версии 4.2.3## Warning: пакет 'lubridate' был собран под R версии 4.2.3## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(ggplot2)
# https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
beaver2## day time temp activ
## 1 307 930 36.58 0
## 2 307 940 36.73 0
## 3 307 950 36.93 0
## 4 307 1000 37.15 0
## 5 307 1010 37.23 0
## 6 307 1020 37.24 0
## 7 307 1030 37.24 0
## 8 307 1040 36.90 0
## 9 307 1050 36.95 0
## 10 307 1100 36.89 0
## 11 307 1110 36.95 0
## 12 307 1120 37.00 0
## 13 307 1130 36.90 0
## 14 307 1140 36.99 0
## 15 307 1150 36.99 0
## 16 307 1200 37.01 0
## 17 307 1210 37.04 0
## 18 307 1220 37.04 0
## 19 307 1230 37.14 0
## 20 307 1240 37.07 0
## 21 307 1250 36.98 0
## 22 307 1300 37.01 0
## 23 307 1310 36.97 0
## 24 307 1320 36.97 0
## 25 307 1330 37.12 0
## 26 307 1340 37.13 0
## 27 307 1350 37.14 0
## 28 307 1400 37.15 0
## 29 307 1410 37.17 0
## 30 307 1420 37.12 0
## 31 307 1430 37.12 0
## 32 307 1440 37.17 0
## 33 307 1450 37.28 0
## 34 307 1500 37.28 0
## 35 307 1510 37.44 0
## 36 307 1520 37.51 0
## 37 307 1530 37.64 0
## 38 307 1540 37.51 0
## 39 307 1550 37.98 1
## 40 307 1600 38.02 1
## 41 307 1610 38.00 1
## 42 307 1620 38.24 1
## 43 307 1630 38.10 1
## 44 307 1640 38.24 1
## 45 307 1650 38.11 1
## 46 307 1700 38.02 1
## 47 307 1710 38.11 1
## 48 307 1720 38.01 1
## 49 307 1730 37.91 1
## 50 307 1740 37.96 1
## 51 307 1750 38.03 1
## 52 307 1800 38.17 1
## 53 307 1810 38.19 1
## 54 307 1820 38.18 1
## 55 307 1830 38.15 1
## 56 307 1840 38.04 1
## 57 307 1850 37.96 1
## 58 307 1900 37.84 1
## 59 307 1910 37.83 1
## 60 307 1920 37.84 1
## 61 307 1930 37.74 1
## 62 307 1940 37.76 1
## 63 307 1950 37.76 1
## 64 307 2000 37.64 1
## 65 307 2010 37.63 1
## 66 307 2020 38.06 1
## 67 307 2030 38.19 1
## 68 307 2040 38.35 1
## 69 307 2050 38.25 1
## 70 307 2100 37.86 1
## 71 307 2110 37.95 1
## 72 307 2120 37.95 1
## 73 307 2130 37.76 1
## 74 307 2140 37.60 1
## 75 307 2150 37.89 1
## 76 307 2200 37.86 1
## 77 307 2210 37.71 1
## 78 307 2220 37.78 1
## 79 307 2230 37.82 1
## 80 307 2240 37.76 1
## 81 307 2250 37.81 1
## 82 307 2300 37.84 1
## 83 307 2310 38.01 1
## 84 307 2320 38.10 1
## 85 307 2330 38.15 1
## 86 307 2340 37.92 1
## 87 307 2350 37.64 1
## 88 308 0 37.70 1
## 89 308 10 37.46 1
## 90 308 20 37.41 1
## 91 308 30 37.46 1
## 92 308 40 37.56 1
## 93 308 50 37.55 1
## 94 308 100 37.75 1
## 95 308 110 37.76 1
## 96 308 120 37.73 1
## 97 308 130 37.77 1
## 98 308 140 38.01 1
## 99 308 150 38.04 1
## 100 308 200 38.07 1summary(beaver2)## day time temp activ
## Min. :307.0 Min. : 0 Min. :36.58 Min. :0.00
## 1st Qu.:307.0 1st Qu.:1128 1st Qu.:37.15 1st Qu.:0.00
## Median :307.0 Median :1535 Median :37.73 Median :1.00
## Mean :307.1 Mean :1446 Mean :37.60 Mean :0.62
## 3rd Qu.:307.0 3rd Qu.:1942 3rd Qu.:37.98 3rd Qu.:1.00
## Max. :308.0 Max. :2350 Max. :38.35 Max. :1.00gr_beaver <- ggplot(data = beaver2, aes(x = time, y = temp)) +
geom_line() +
geom_point()
gr_beaver
ирисы
library(tidyverse)
library(ggplot2)
library(ggpubr)## Warning: пакет 'ggpubr' был собран под R версии 4.2.3# https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
#https://r-graph-gallery.com
#https://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
#install.packages("ggpubr")
summary(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width
## Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100
## 1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300
## Median :5.800 Median :3.000 Median :4.350 Median :1.300
## Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
## 3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
## Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
## Species
## setosa :50
## versicolor:50
## virginica :50
##
##
## iris_s <- iris %>% filter(Species != "setosa")
gr_iris<- ggplot(data = iris_s,
aes(x = Species, y = Sepal.Length, color = Species)) +
geom_boxplot() +
geom_jitter(width = 0.25) +
stat_compare_means() +
xlab("Вид")
gr_iris
ggsave("gr_iris.png", width = 6, height = 6)