Preliminary Data Analysis. Explore the dataset and practice extracting basic observations about the data. The idea is for you to get comfortable working in R.
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Description
Objective -
Preliminary Data Analysis. Explore the dataset and practice extracting basic
observations about the data. The idea is for you to get comfortable working in
R.
You are expected to do
the following :
1. Come up
with a customer profile (characteristics of a customer) of the different
products
2. Perform
uni-variate and bivariate analyses
3. Generate
a set of insights and recommendations that will help the company in targeting
new customers
Context -
The data is for customers of the treadmill product(s) of a retail store called
Cardio Good Fitness. It contains the following variable
1. Product
- the model no. of the treadmill
2. Age -
in no of years, of the customer
3. Gender
- of the customer
4. Education
- in no. of years, of the customer
5. Marital
Status - of the customer
6. Usage -
Avg. # times the customer wants to use the treadmill every week
7. Fitness
- Self rated fitness score of the customer (5 - very fit, 1 - very unfit)
8. Income
- of the customer
9. Miles-
expected to run
Explore the dataset to
identify differences between customers of each product. You can also explore
relationships between the different attributes of customers. You can approach
it from any other line of questioning that you feel could be relevant for
business.
Minimum Steps for
exploration:
1. Importing
the dataset into R & understanding the structure of a dataset
2. Basic
summary of data and graphical exploration
3. Observations from
the dataset
Submission Guidelines :
1. You can
submit the output/report in any file format - the key part of the output is the
set of observations from the exploration
2. Please
don’t share your R code and/or outputs only, we expect some verbiage/story too
- a meaningful output that you can share in a business environment
Grading Criteria:
|
Component |
60 |
% weightage |
|
Understanding the structure of the
data |
3 |
5% |
|
Univariate analysis |
12 |
20% |
|
Bivariate analysis |
15 |
25% |
|
Quality & use of
visualisations |
9 |
15% |
|
Conclusion |
15 |
25% |
|
R Code |
6 |
10% |
Thanks
Program Office
Rubric
Cardio Fitness Rubric
|
Cardio
Fitness Rubric |
||
|
Criteria |
Ratings |
Pts |
|
This criterion is linked to a Learning OutcomeUnderstanding
the structure of the data |
3.0 pts |
|
|
This criterion is linked to a Learning OutcomeUnivariate
analysis |
12.0 pts |
|
|
This criterion is linked to a Learning OutcomeBivariate
analysis |
15.0 pts |
|
|
This criterion is linked to a Learning OutcomeQuality
& use of visualisations |
9.0 pts |
|
|
This criterion is linked to a Learning OutcomeConclusion |
15.0 pts |
|
|
This criterion is linked to a Learning OutcomeR
Code |
6.0 pts |
|
|
Total Points: 60.0 |
||
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