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(
x = Statistic,
y = Math,
main = "班上的統計成績與數學成績",
xlab = "統計成績",
ylab = "數學成績",
pch = 10,
col = "lightblue",
cex = 1.5
)
# Add grid lines
grid()
Statistic <- c(68, 85, 74, 88, 63, 78, 90, 80, 58, 63)
hist(
Statistic,
main = "班上的體重與身高",
xlab = "體重",
ylab = "次數",
col = "lightyellow",
border = "black",
breaks = seq(55, 90, by = 5),
cex.main = 1.5,
cex.lab = 1.2,
cex.axis = 1.1
)
coding <- c("5", "4", "3", "2", "1")
frequencies <- c(185, 82, 36, 28, 25)
barplot(
frequencies,
names.arg = coding,
main = "頻數長條圖",
xlab = "分類",
ylab = "頻數",
col = "lightblue",
border = "black",
cex.main = 1.5,
cex.lab = 1.2,
cex.axis = 1.1
)
coding <- c("5", "4", "3", "2", "1")
frequencies <- c(185, 82, 36, 28, 25)
pie(
frequencies,
labels = coding,
main = "頻數圓餅圖",
col = c("blue", "green", "yellow", "pink", "gray"),
border = "black",
cex.main = 1.5,
cex.lab = 1.2
)
data2 <- read.csv("D:/table1_1.csv")
print(data2)
## Name Statistic Math Japanese Management Accounting
## 1 張青松 68 85 84 89 86
## 2 王奕翔 85 91 63 76 66
## 3 田新雨 74 74 61 80 69
## 4 徐麗娜 88 100 49 71 66
## 5 張志傑 63 82 89 78 80
## 6 趙穎睿 78 84 51 60 60
## 7 王智強 90 78 59 72 66
## 8 宋媛婷 80 100 53 73 70
## 9 袁四方 58 51 79 91 85
## 10 張建國 63 70 91 85 82
stem(data2$Japanese)
##
## The decimal point is 1 digit(s) to the right of the |
##
## 4 | 9
## 5 | 139
## 6 | 13
## 7 | 9
## 8 | 49
## 9 | 1
data <- read.csv("D:/table1_1.csv")
japanese_data <- data$Japanese
mean_japanese <- mean(japanese_data, na.rm = TRUE)
median_japanese <- median(japanese_data, na.rm = TRUE)
getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
}
mode_japanese <- getmode(japanese_data)
sd_japanese <- sd(japanese_data, na.rm = TRUE)
variance_japanese <- var(japanese_data, na.rm = TRUE)
q1_japanese <- quantile(japanese_data, 0.25, na.rm = TRUE)
cat("1. 平均數 (Mean):", mean_japanese, "\n")
## 1. 平均數 (Mean): 67.9
cat("2. 中位數 (Median):", median_japanese, "\n")
## 2. 中位數 (Median): 62
cat("3. 眾數 (Mode):", mode_japanese, "\n")
## 3. 眾數 (Mode): 84
cat("4. 標準差 (Standard Deviation):", sd_japanese, "\n")
## 4. 標準差 (Standard Deviation): 16.25115
cat("5. 變異數 (Variance):", variance_japanese, "\n")
## 5. 變異數 (Variance): 264.1
cat("6. Q1 第一四分位數 (Q1):", q1_japanese, "\n")
## 6. Q1 第一四分位數 (Q1): 54.5
data <- read.csv("D:/table1_1.csv")
japanese_data <- data$Japanese
mean_japanese <- mean(japanese_data, na.rm = TRUE)
median_japanese <- median(japanese_data, na.rm = TRUE)
getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
}
mode_japanese <- getmode(japanese_data)
sd_japanese <- sd(japanese_data, na.rm = TRUE)
variance_japanese <- var(japanese_data, na.rm = TRUE)
q1_japanese <- quantile(japanese_data, 0.25, na.rm = TRUE)
q3_japanese <- quantile(japanese_data, 0.75, na.rm = TRUE)
cat("1. 平均數 (Mean):", mean_japanese, "\n")
## 1. 平均數 (Mean): 67.9
cat("2. 中位數 (Median):", median_japanese, "\n")
## 2. 中位數 (Median): 62
cat("3. 眾數 (Mode):", mode_japanese, "\n")
## 3. 眾數 (Mode): 84
cat("4. 標準差 (Standard Deviation):", sd_japanese, "\n")
## 4. 標準差 (Standard Deviation): 16.25115
cat("5. 變異數 (Variance):", variance_japanese, "\n")
## 5. 變異數 (Variance): 264.1
cat("6. Q1 第一四分位數 (Q1):", q1_japanese, "\n")
## 6. Q1 第一四分位數 (Q1): 54.5
cat("7. Q3 第三四分位數 (Q3):", q3_japanese, "\n")
## 7. Q3 第三四分位數 (Q3): 82.75