Lecture notes and solutions to the exercises of session 2 in the fall semester 2022

#T2 - Lecture notes (FaSe22)

 Lecture notes and solutions to the exercises of session 2 in the fall semester 2022

Session2-ExerciseSolutions.R

# Solutions to the in-class exercises of session 2

# Exercise 2.1 (slide 9)---------------
# Convention: white space between + or -,
#  but no white space between *, **, and /
5 + 12
(2*3)**2
2*5.8
(8**2 + 5**4)/3

# Exercise 2.2 (slide 16)--------------
# I used these names to avoid using 'c' as a name
#  since c() is also a function
a_ <- 2 +3
b_ <- (5*a_) / 2
c_ <- (b_+1)**2
d_ <- c_**0.5
d_

# Function exercises I (slide 24)------
f_vec <- c(-2, 2, 3, 6, 9, NA)
median(f_vec)
median(f_vec, rm.na=TRUE)
is.na(f_vec) # Tests each element for NA
anyNA(f_vec) # Tests whether vector contains at least one NA
sum(f_vec)
sum(f_vec, rm.na=TRUE)

# From the help function you may know that 
#  var() computes sample variances
var_vec <- c(1, 6, 7, 9, 12)
sample_var <- var(var_vec)
# To get the population variance:
# Determine length of data
n_elements <- length(sample_var)
pop_var <- var(sample_var)*(n_elements - 1)/n_elements
# See, e.g., here: https://stackoverflow.com/a/37733398

sample_var
pop_var

# Function exercises II (slide 28)-----

#' Normalize a vector into 0-1 range
#' 
#' This function takes a vector and normalizes its elements into the range 
#'  between 0 and 1. It does not yet handle special cases, such as vectors with
#'  missing values, but we learn how to deal with this later on.
#' @param x_vector A vector without missing values
#' @returns A vector with the same number of elements as `x_vector`, but 
#'  normalized into the 0-1 range
norm_function <- function(x_vector){
  min_value <- min(x_vector)
  max_value <- max(x_vector)
  result <- (x_vector - min_value) / (max_value - min_value)
  return(result)
}

# Example application:
vec_used <- c(1, 2, 3, 4, 5, 6, -2)
vec_used_normed <- norm_function(vec_used)
vec_used_normed

# Note that all values defined within the function are not available after
#  calling it:
max_value

Session2-Notes.R

# Session 2 notes
# These are all notes that I have taken during the lecture
#  Solutions for the exercises can be found in a separate script

# Assignments--------------------------

assign("intermediate_result", 2 + 3)
assign("complicated_result", (8**2 + 5**4) / 3)

assign("other_result", (2*3)**2)
other_result <- (2*3)**2 # Equivalent to line 10

other_result = (2*3)**2 # Do never do that!!!

rm(other_result)

# Many names, one object?--------------
a_name <- 2*2
b_name <- 2*2
a_name
b_name

# Many objects, one name?--------------
c_name <- 2*3
c_name <- 2*4