STAT 432: Analysis 03
Directions
IMRAD and Quiz Due: Monday, November 18, 3:00 PM
Reflection Due: Thursday, November 21, 3:00 PM
Analysis Goal
Use the given data to detect the credit card fraud. There are three tasks associated with
this analysis:
Quiz Subset Data: cc-sub.csv (data/cc-sub.csv)
Full Data: creditcard.csv.gz (https://stat432.org/data/creditcard.csv.gz)
Use:
readr::read_csv("https://stat432.org/data/creditcard.csv.gz")
to read the full data directly.
Source: Kaggle - Credit Card Fraud Detection (https://www.kaggle.com/mlgulb/creditcardfraud)
Please refer to the source documentation for information on data collect and a data
dictionary. The response was altered.
0 is now labeled genuine
1 is now labeled fraud
The following code is available to show how the quiz data was created, but please use
the .csv linked above. If you choose to use the full data, you will need to run the line
below that alters the response from 0 and 1 to genuine and fraud , unless you
prefer 0 and 1 .
# load pacakges
library("tidyverse")
library("caret")
library("gbm")
library("ROSE")
# extract file obtained from Kaggle
# https://www.kaggle.com/mlg-ulb/creditcardfraud
untar("creditcardfraud.zip")
# create remote readable compressed file
system("gzip creditcard.csv")
# from gz file
cc = read_csv("creditcard.csv.gz")
# verify data
nrow(cc) == 284807
# make response a factor with names instead of numbers
cc$Class = factor(ifelse(cc$Class == 0, "genuine", "fraud"))
# subset for efficiency and PL
set.seed(42)
sub_idx = sample(nrow(cc), size = 50000)
cc_sub = cc[sub_idx, ]
# write subset to disk
write_csv(cc_sub, "cc-sub.csv")
IMRAD
For this analysis, do the following:
Analyze the data however your please! You should keep the stated goal in mind,
but you may define a more specific goal that you are working towards.
Write a report in R Markdown using the IMRAD
(https://en.wikipedia.org/wiki/IMRAD) template
(https://www.cmu.edu/gcc/handouts-and-resources/handouts/imrd.pdf).
Write an abstract.
Write an introduction.
Write an methods section.
Write an results section.
Write an discussion.
IMRAD Submission
Submit a .zip file to Compass that contains:
A .Rmd file that is your IMRAD.
This file should be written assuming that it is in the same folder as a folder
called /data/ which contains heart-disease.csv .
Hint: Create an RStudio Project.
A .html file that is the result of knitting your .Rmd file.
The zip file should contain no other files. (Whether or not these two files are within
another folder does not matter.)
Submit your .zip file to the correct assignment on Compass2g. You are granted an
unlimited number of submissions. Only your final submission will be graded.
R Environment
We assume that your R , R packages, and RStudio are all up-to-date. (Or at least as
recent as the versions found on RStudio Cloud.) You’ve been warned.
R Style
Your code will be graded based on its style. We don’t expect you to have a mature
coding style, so we have a list of rules which must be followed.
The following will be explicitly checked for in your code:
All commas must be followed by a space. (Additionally, commas should never be
preceded by a space.)
Infix operators ( == , + , - , <- , etc.) should always be surrounded by spaces.
(https://style.tidyverse.org/syntax.html#infix-operators)
Exceptions: : , :: , $ , [ , [[ , ] , ]]
^ : Use x ^ 2 instead of x^2 .
Use a consistent assignment operator. Either <- or = , not both.
If you choose to use the <- operator, you will need to replace the =
operator in the given code.
Do not use T or F .
Do not use absolute paths.
Do not use semicolons, ; .
Do not use the attach() function.
No more than one newline (blank line) in a row in an R Markdown document.
No more than one newline (blank line) in a row in an R chunk.
A newline before and after each chunk in an R Markdown document.
No newline to start a chunk. No newline at end of chunk. (The first and last line of
each chunk should contain code, or a comment for the first line.)
A newline at the end of the file.
The following are suggested, but will not be directly assessed:
Variable and function names (that are user created) should only contain lowercase
letters, numbers, and underscores.
Do not use periods, . , or capital letters in variable and function names.
Opening (left) curly braces should not be on their own line.
A space should precede a parenthesis, except in a function call.
Good: for (i in 1:10)
Bad: for(i in 1:10)
Good: mean(x)
Bad: mean (x)
Except for the first, argument names should be written in function calls.
(Exception for the predict() function.)
This will be encouraged, but not enforced, as often it is better to make a
judgement call than to be dogmatic.
Much of this is derived from the tidyverse style guide (https://style.tidyverse.org). If
you follow the tidyverse guide, be aware of our use of ^ and = .
Analysis Quiz
There will be a PL quiz associated with this analysis to check some of the “objective”
numeric results of your analysis.
Self Assessment
After submission of the analysis, an example “solution” will be released. In addition, a
set of reflection questions will be released. By comparing your submitted analysis to the
“solution” together with the reflection questions, you will write a short self-assessment of
you analysis.
Specifics on formatting, submission, etc, will be released after the analysis is due.
Grading
This analysis is worth a total of 10 points.
IMRAD .Rmd and .html (4 points)
Code Style in .Rmd (0 - 1 - 2)
Eye Test of .html (0 - 1 - 2)
Does it look like you’ve done an analysis? Is it reasonably formatted?
Analysis Quiz (4 points)
Reflection (2 points)
Failure to submit the correct files will results in 0 points for the IMRAD.
Quiz grading will be similar to regular quizzes.
Grading of the self reflection will largely be based on completion. A template will be
provided after submission of the analysis.
Late Policy
The late policy will apply to each individual task. See above for due dates.
Late submissions for both will be accepted up to 48 hours after the initial deadline.
Up to 24 hours late, the assignment will incur a 10 percent reduction.
Up to 48 hours late, the assignment will incur a 30 percent reduction.
No exceptions! Start early and make sure your environment is working correctly
and you are able to produce a working document.
If you submit multiple attempts, the final attempt will be graded. If your first submission
is on time, but your final submission is late, you will incur the late submission penalty.