【浙工商期末报告】研一R语言期末作业（源代码分享）

不念不忘少年蓝@ 2023-09-27 13:26 57阅读 0赞

#### 目录：研一R语言期末作业（源代码分享） ####

*  一、作业回顾
 *   *  1.1 计算t值
     *  1.2 绘图
 *  二、结果展示
 *   *  2.1 计算t值
     *  2.2 绘图
 *  三、源代码分享

## 一、作业回顾 ##

### 1.1 计算t值 ###

![在这里插入图片描述][f5054b15bffc4cdcb78b4794cb7d9412.jpeg]

### 1.2 绘图 ###

![在这里插入图片描述][bde968168cf844938167b0ea56863107.jpeg]

## 二、结果展示 ##

### 2.1 计算t值 ###

\[1\] -1.937926

### 2.2 绘图 ###

\[1\] “1974-03-01” “1974-06-01” “1974-09-01” “1974-12-01” “1975-03-01”  
\[6\] “1975-06-01” “1975-09-01” “1975-12-01” “1976-03-01” “1976-06-01”  
\[11\] “1976-09-01” “1976-12-01” “1977-03-01” “1977-06-01” “1977-09-01”  
\[16\] “1977-12-01” “1978-03-01” “1978-06-01” “1978-09-01” “1978-12-01”  
\[21\] “1979-03-01” “1979-06-01” “1979-09-01” “1979-12-01”  
![在这里插入图片描述][0fccccb207494cecb331c9a49c95ea96.png]

## 三、源代码分享 ##

sink("./23.R-Project/R软件与数据分析测试.doc", append = TRUE, split = TRUE)
    
    # 第一问,定义函数求解t值
    
    tst <- function(x, y) {
        
        x_mean <- mean(x)
        y_mean <- mean(y)
        x_std <- sd(x) * sd(x)
        y_std <- sd(y) * sd(y)
        m <- length(x)
        n <- length(y)
        s_p <- sqrt(((m - 1) * x_std + (n - 1) * y_std) / (m + n - 2))
        t_value <- ((x_mean - y_mean) / (s_p * (sqrt(1 / m + 1 / n))))
        return(t_value)
    }
    x <- c(1, 4, 3, 6, 5)
    y <- c(5, 4, 7, 6, 10)
    print(tst(x, y))
    
    
    # 第二问,绘图
    
    data <- read.table('./23.R-Project/mydata1.txt', header = TRUE,  sep = '	',  stringsAsFactors = FALSE)
    data[,1] <- gsub('Q1', '-03-01', data[,1])
    data[,1] <- gsub('Q2', '-06-01', data[,1])
    data[,1] <- gsub('Q3', '-09-01', data[,1])
    data[,1] <- gsub('Q4', '-12-01', data[,1])
    data[,1] <- as.Date(data[,1], format = '%Y-%m-%d')
    print(data[, 1])
    
    par(mfrow = c(2, 2))
    Time <- data[, 1]
    
    plot(Time, data[,2], type = "b", pch = 16, lty = 1, main = "line plot",ylab = "")
    lines(Time, data[,3], type = "b", pch = 17, lty = 3)
    legend("topleft", inset = .05, title = "country", c("UK", "US"), lty = c(1, 3), pch = c(16, 17))
    library(reshape2)
    data2 <- melt(data, id = 'time')
    
    boxplot(data2[,3]~data2[,2], data, main = 'box plot', ylab = 'value', xlab = 'value')
    
    hist(data[,2], freq = F, main = 'Histogram and Density Curve', xlab = 'puk')
    lines(density(data[,2]))
    
    h <- hist(data[,3], xlab = "pus", main = "Histogram with Normal Curve")
    x <- seq(min(data[,3]), max(data[,3]), length = 40)
    y <- dnorm(x, mean(data[,3]), sd(data[,3]))
    y <- y * diff(h$mids[1:2]) * length(data[,3])
    lines(x, y)
    
    sink()

[f5054b15bffc4cdcb78b4794cb7d9412.jpeg]: https://img-blog.csdnimg.cn/f5054b15bffc4cdcb78b4794cb7d9412.jpeg
[bde968168cf844938167b0ea56863107.jpeg]: https://img-blog.csdnimg.cn/bde968168cf844938167b0ea56863107.jpeg
[0fccccb207494cecb331c9a49c95ea96.png]: https://img-blog.csdnimg.cn/0fccccb207494cecb331c9a49c95ea96.png