1112203004

statistic_scores <- c(68, 85, 74, 88, 63, 78, 90, 80, 58, 63)
math_scores <- c(85, 91, 74, 100, 82, 84, 78, 100, 51, 70)

plot(statistic_scores, math_scores, 
     main = "統計成績與數學成績散佈圖", 
     xlab = "統計成績", ylab = "數學成績", 
     col = "blue", pch = 16)

hist(statistic_scores, 
     main = "統計成績的直方圖", 
     xlab = "統計成績", 
     col = "green", breaks = 5)

categories <- c("0-10", "11-20", "21-30", "31-40", "41-50", "51-60")
frequencies <- c(2, 6, 10, 8, 6, 4)

barplot(frequencies, names.arg = categories, 
        main = "次數分配的長條圖", 
        xlab = "範圍", ylab = "次數", 
        col = "orange")

pie(frequencies, labels = categories, 
    main = "次數分配的圓餅圖", 
    col = rainbow(length(categories)))

data <- read.csv("table1_1.csv")
stem(data$Japanese)

## 
##   The decimal point is 1 digit(s) to the right of the |
## 
##   4 | 9
##   5 | 139
##   6 | 13
##   7 | 9
##   8 | 49
##   9 | 1

mean_japanese <- mean(data$Japanese)
median_japanese <- median(data$Japanese)
mode_japanese <- as.numeric(names(sort(table(data$Japanese), decreasing = TRUE)[1]))
sd_japanese <- sd(data$Japanese)
var_japanese <- var(data$Japanese)
q1_japanese <- quantile(data$Japanese, 0.25)
q3_japanese <- quantile(data$Japanese, 0.75)

cat("Japanese變項的統計量：\n")

## Japanese變項的統計量：

cat("平均數：", mean_japanese, "\n")

## 平均數： 67.9

cat("中位數：", median_japanese, "\n")

## 中位數： 62

cat("眾數：", mode_japanese, "\n")

## 眾數： 49

cat("標準差：", sd_japanese, "\n")

## 標準差： 16.25115

cat("變異數：", var_japanese, "\n")

## 變異數： 264.1

cat("第一四分位數(Q1)：", q1_japanese, "\n")

## 第一四分位數(Q1)： 54.5

cat("第三四分位數(Q3)：", q3_japanese, "\n")

## 第三四分位數(Q3)： 82.75