Rで学ぶA/Bテスト
Lauryn Burleigh
Data Scientist
可視化するもの:
library(dplyr) data <- pizza %>% group_by(Topping) %>% summarise(AvgTime = mean(Time), SdTime = sd(Time))
library(dplyr) data <- pizza %>% group_by(Topping) %>%
summarise(AvgTime = mean(Time), SdTime = sd(Time))
data
# A tibble: 2 × 3 Topping AvgTime SdTime <chr> <dbl> <dbl> 1 Cheese 5.81 0.948 2 Pepperoni 6.46 1.06
library(ggplot2) ggplot(data, aes(x = Topping, y = AvgTime, fill = Topping)) + geom_bar(stat = "summary", fun = "mean") + geom_errorbar(aes( ymin = AvgTime - SdTime, ymax = AvgTime + SdTime))
library(ggplot2)
ggplot(data, aes(x = Topping,
y = AvgTime,
fill = Topping)) +
geom_bar(stat = "summary", fun = "mean") +
geom_errorbar(aes( ymin = AvgTime - SdTime, ymax = AvgTime + SdTime))
ggplot(pizza, aes(x = Topping, y = Time, fill = Topping)) + geom_boxplot()
ggplot(pizza, aes(x = Topping, y = Time, fill = Topping)) +
geom_boxplot()
library(ggplot2) ggplot(pizza, aes(x = Time, y = Enjoyment, fill = Topping)) + geom_point()
library(ggplot2) ggplot(pizza, aes(x = Time, y = Enjoyment, fill = Topping)) +
geom_point()
ggplot(subset(pizza, Topping %in% "Pepperoni"), aes(x = Time, y = Enjoy)) + geom_point()
統計の前提知識がない聴衆向け:
結果:
発表内容:
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