Description
Overview
Collaboration: Do your work and report individually. You can collaborate on the right tools to
use and setting up your programming environment.
Hand in: One report per person, via the LEARN dropbox. Also submit the code / scripts needed
to reproduce your work. Report as a PDF or a python notebook.
General Objective: To study how to apply some of the methods discussed in class on two
datasets. The emphasis is on analysis and presentation of results not on code implemented
or used.
Specific Objectives: • Establish your software stack to carry out data analysis homeworks,
assignments and the project for the rest of the course.
• Load a simple dataset and compute some basic statistics and plots.
Tools: You can use libraries available in python or R available to you. You need to mention which
libraries you are using, any blogs or papers you used to figure out how to set carry out your
calculations.
Data sets
This is your first homework so there are two datasets.
• The Breast Cancer Wisconsin (Diagnostic) Data Set
– https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)
– Download from Data Folder link, read data set description.
• Class Anonymous Poll (optional)
– Fill out the poll first with your own answers https://goo.gl/forms/iFYBlz9H6QsY9GUS2
– Download data from https://docs.google.com/spreadsheets/d/1fOSqZsINRnx8Pp0pEPhNfuFsMMo3sQNn_
lA5UoUnHnU/edit?usp=sharing (will not be available until poll is closed)
Tasks
In the first class we talked about how to summarize single-variable data, how to compute the
Pearson Correlation Coefficient for pairs of points
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• In the cancer dataset report the mean, mode and skew, standard deviation and variance values
for all the continuous valued features.
• In the cancer dataset s a few pairs of features for correlation by computing their PCC and
report the resulting numbers and explain what they mean.
• In the cancer dataset plot two histograms for a continuous valued feature of your choice: One
for patients with each diagnosis (M or B).
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