This assignment is to provide you with the hands-on practice of using R to do data cleaning and transformation as well as practicing on visualizations with your choice of tools.
Submission This assignment (codes and report) must be completed and submitted by 2359 on the last working day before the next lesson. Any late submissions will be deemed incomplete and will not be accepted.
This assignment is to be done on an individual basis and any attempt at sharing results / code / findings / data / analysis / text or through any forms / medium by which the works is found to be not done by the individual – the assignment will be deemed as incomplete and will not be accepted.
Code submissions • must be made to each individual Github account and made accessible. Accounts that cannot be accessed will have their codes deemed as incomplete and assignment scored as such. • that cannot be executed (portions or on the whole) will be deemed as incomplete and assignment will be scored as such.
Data Description
This data set is from the Global Competitiveness Report (GCR) 2014 conducted by the World Economic Forum. There are many pillars covered in this report (e.g. public institutions, health, education, labor market efficiency and etc). The GCR assesses the ability of countries to provide high levels of prosperity to their citizens.
In this assignment, we will be looking only at the following countries, series and variables:
Countries:
- Cambodia
- Indonesia
- Malaysia
- Philippines
- Singapore
- Thailand
- Vietnam
Series:
- Diversion of Public Funds
- Irregular Payments and Bribes
- Reliability of Police Services
- Inflation
- Soundness of Banks
- HIV Prevalence
- Quality of the Education System
- Primary, Secondary and Tertiary Education Enrollment
- GDP (US$ Billions)
- GDP per capita
- Domestic and Foreign Market Size Index
Variables:
- Series Code
- Series
- Value
- Rank
The codebook “WEF_GlobalCompetitivenessReport_2014-15.pdf” will provide an explanation on the variables and the description of the values.
You will need to read in the XLSX / CSV file in R, clean and transform the dataset and then work on the specific variables as described above. Support your answers for each question with visualization(s). You are free to choose any tools which you would like to use to render your visualization(s).