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


plot(Statistic, Math,
     main = "統計成績與數學成績之散佈圖",
     xlab = "統計成績",
     ylab = "數學成績",
     pch = 16,           
     col = "darkgreen",  
     cex = 1.5)         
grid()

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

# 畫出數學成績直方圖
hist(Math,
     main = ,
     xlab = ,
     ylab = ,
     col = "lightblue",
     border = "black")

club_type <- c("娛樂休閒", "知識閱讀", "體育競技", "科學創新", "公益活動")
frequency <- c(185, 82, 36, 28, 25)

# 繪製長條圖
barplot(frequency,
        names.arg = club_type,
        main = ,
        xlab = ,
        ylab = ,
        col = "skyblue",
        border = "darkblue")

# 建立資料
club_type <- c("娛樂休閒", "知識閱讀", "體育競技", "科學創新", "公益活動")
frequency <- c(185, 82, 36, 28, 25)

# 加上標籤
labels <- paste(club_type, "(", frequency, ")", sep="")

# 繪製圓餅圖
pie(frequency,
    labels = labels,
    main = "大學生最喜歡參加的社團類型(圓餅圖)",
    col = rainbow(length(frequency)))

# 資料
club_type <- c("娛樂休閒", "知識閱讀", "體育競技", "科學創新", "公益活動")
frequency <- c(185, 82, 36, 28, 25)

# 棒棒糖圖
plot(frequency,
     type = "n",  # 不先畫點
     xaxt = "n",  # 不畫 x 軸
     main = "大學生最喜歡參加的社團類型",
     xlab = "社團類型",
     ylab = "次數",
     ylim = c(0, max(frequency) + 20))

# 畫棒棒糖的線(棒子)
segments(x0 = 1:5, y0 = 0, x1 = 1:5, y1 = frequency, col = "skyblue", lwd = 2)

# 畫棒棒糖的頭(糖果球)
points(1:5, frequency, pch = 16, col = "blue", cex = 2)

# 加上 X 軸標籤
axis(1, at = 1:5, labels = club_type)

data <- read.csv("C:/Users/wenzao/Downloads/table1_1.csv")


if ("Japanese" %in% colnames(data)) {

  stem(data$Japanese)
} else {
  print("找不到 Japanese 欄位,請確認檔案內容是否正確。")
}
## 
##   The decimal point is 1 digit(s) to the right of the |
## 
##   4 | 9
##   5 | 139
##   6 | 13
##   7 | 9
##   8 | 49
##   9 | 1
data <- read.csv("C:/Users/wenzao/Downloads/table1_1.csv")




names(data)  # 確保有 "Japanese" 欄位
## [1] "Name"       "Statistic"  "Math"       "Japanese"   "Management"
## [6] "Accounting"
japanese <- data$Japanese


mean_jp <- mean(japanese)

# 中位數
median_jp <- median(japanese)


get_mode <- function(x) {
  uniq_vals <- unique(x)
  uniq_vals[which.max(tabulate(match(x, uniq_vals)))]
}
mode_jp <- get_mode(japanese)


sd_jp <- sd(japanese)


var_jp <- var(japanese)


q1_jp <- quantile(japanese, 0.25)


q3_jp <- quantile(japanese, 0.75)


result <- data.frame(
  統計量 = c("平均數", "中位數", "眾數", "標準差", "變異數", "第一四分位數", "第三四分位數"),
  數值 = c(mean_jp, median_jp, mode_jp, sd_jp, var_jp, q1_jp, q3_jp)
)

print(result)
##         統計量      數值
## 1       平均數  67.90000
## 2       中位數  62.00000
## 3         眾數  84.00000
## 4       標準差  16.25115
## 5       變異數 264.10000
## 6 第一四分位數  54.50000
## 7 第三四分位數  82.75000