--- title: "R Notebook For Code Execution" output: html_document: toc: true toc_depth: 2 toc_float: true --- The following provided code should be used to make sure that: - you have the required packages installed; - you can run a python script from an outside source and get back an example dataset and plot. The datasets in this notebook are not representative of ones in the Midterms/Exam - see the exercises in the lecture notes for such data examples. If something does not work - make sure to find out **before your midterm**. ## Some Required Libraries You may need the following libraries: ```{r} suppressPackageStartupMessages({ suppressWarnings({ suppressMessages({ library(lmtest) library(tseries) }) }) }) ``` You can also add any other libraries that you will be using. ## Setting your Student code Below you should input your student code and run the code source. It should provide a small plot on succesfull completion. Before that, make sure you define your `STUDENT_CODE`: ```{r} STUDENT_CODE <- YOUR_STUDENT_CODE ``` ## Loading Functions and Data From the Notebook The following functions will generate a dataset: ```{r} plot_student <- function(student_code, nn){ par(mar = c(0,0,0,0)) plot(c(0, 1), c(0, 1), ann = F, bty = 'n', type = 'n', xaxt = 'n', yaxt = 'n') rect(0.2, 0.4, 0.8, 0.6, col = "khaki1") center <- c(mean(c(0.2, 0.8)), mean(c(0.4, 0.6))) text(x = center[1] / 2.5, y = center[2], paste0("Student: ", student_code, "\nDataset size: ", nn), cex = 1.6, col = "black", pos = 4) par(mfrow = c(1,1)) } ``` ```{r} genr_data <- function(s_code){ set.seed(s_code) # N <- sample(seq(from = 100, to = 300, length.out = 9), size = 1) x <- rnorm(mean = 12, sd = 4, n = N) e <- rnorm(mean = 0, sd = 0.51, n = N) y <- 1 + 2 * x + e # DT <- data.frame(x = x, y = y) # # plot_student(s_code, N) # return(DT) } ``` The above function(-s) will be called for initial data generation. --- --- ### Data Example Run the following code to generate data for your `STUDENT_CODE` via the above functions: ```{r} DT1 = genr_data(STUDENT_CODE) ``` Your dataset should have some data: ```{r} print(head(DT1)) ``` ```{r} print(summary(DT1)) ```