CODE in R

Train.r:

# Delete everything out of the environment

rm(list=ls())

# Does the script use require, library, or :: package?

#

rl

if (any(grepl("library", rl)) |

any(grepl("require", rl)) |

any(grepl("::", rl, fixed = TRUE))) {

stop("This script may use a non-base package and therefore will receive a score of 0.")

}

# Even if you can get around this issue (by, say, adding the package to your

# .Rprofile file), the script will not work on our computer and therefore you

# will not receive points.

#

# Load functions

source("script.R")

# Points

points

earned = 10,

possible = 10)

# Check for the functions

fxns

"add_even",

"calculate_summary_statistics",

"is_magicsquare")

pts

for (i in seq_len(length(fxns))) {

pts

}

points

data.frame(check = "function names",

earned = pts,

possible = length(fxns)))

#############################################################################

# Check celsius_to_fahrenheit results

#############################################################################

celsius

fahrenheit

points

data.frame(check = "celsius_to_fahrenheit",

earned = sum(celsius_to_fahrenheit(celsius) == fahrenheit),

possible = length(fahrenheit)))

#############################################################################

# Check add_even results

#############################################################################

n

r

stopifnot(length(n) == length(r))

pts

for (i in seq_len(length(n))) {

pts

}

points

data.frame(check = "add_even",

earned = pts,

possible = length(n)))

#############################################################################

# Check is_magicsquare

#############################################################################

squares

matrix(c(2, 7, 6,

9, 5, 1,

4, 3, 8),

byrow = TRUE,

nrow = 3, ncol = 3),

matrix(c(1, 14, 14, 4,

11, 7, 6, 9,

8, 11, 10, 5,

13, 2, 3, 15),

byrow = TRUE,

nrow = 4, ncol = 4),

matrix(c(46, 8, 16, 20, 29, 7, 49,

3, 40, 35, 36, 18, 41, 2,

44, 12, 33, 23, 19, 38, 6,

28, 26, 11, 25, 39, 24, 22,

5, 37, 31, 27, 17, 13, 45,

48, 9, 15, 14, 32, 10, 47,

1, 43, 34, 30, 21, 42, 4),

byrow = TRUE,

nrow = 7, ncol = 7)

)

ms

pts

for (i in 1:length(squares)) {

pts

}

points

data.frame(check = "is_magicsquare",

earned = pts,

possible = length(ms)))

#############################################################################

# Check calculate_summary_statistics() results

#############################################################################

my_near

abs(a-b)

}

# ToothGrowth

s

pts

my_near(s$n, 60),

my_near(s$m, 18.81333),

my_near(s$s, 7.649315),

my_near(s$lcl, 16.83731),

my_near(s$ucl, 20.78936)

)

points

points,

data.frame(

check = "calculate_summary_statistics_ToothGrowth",

earned = pts,

possible = 5)

)

# missing values

vector_with_NAs

s

pts

my_near(s$n, 10),

my_near(s$m, 5.5),

my_near(s$s, 3.02765),

my_near(s$lcl, 3.334149),

my_near(s$ucl, 7.665851)

)

points

points,

data.frame(

check = "calculate_summary_statistics_with_NAs",

earned = pts,

possible = 5)

)

# different significance level

s

pts

my_near(s$lcl, 3.744928),

my_near(s$ucl, 7.255072)

)

points

points,

data.frame(

check = "calculate_summary_statistics_diff_error",

earned = pts,

possible = 2)

)

This assignment will focus on using R as a programming language. The intent of the assignment is to use control flow (e.g. if, else, while, for) as well as functions. You will only be allowed to use base R functions, i.e. functions in the stats, graphics, grDevices, utils, datasets, methods, and base packages. The assignment will be automatically graded, but not using Canvas. You will be required to provide an R script which will be read in using the source() command. This script should be named script.R and contain only functions. Then two scripts will be run to evaluate your functions: train.R and test.R. You will have access to the train.R file so you can see whether you pass the tests or not. Then we will run test.R to see if you pass the hidden tests. Check that the earned column is equal to the possible column. If either source commands produces an error or if the earned column is not equal to the possible column, then you have a bug in your code. (Of course, you may also have a bug in your code that the "train.R" file did not catch.) 4. Construct a function named calculate_summary_statistics() with two arguments: v and a. The function should calculate the following summary statistics for the data in v : - sample size (n) - sample mean (m), - sample standard deviation(s)