Regression Modeling in Practice Week 1 Assignement

I am continuing on with the Coursera Data Analysis and Interpretation Specialization courses. The third course is called Regression Modeling in Practice.  I will be continuing my analysis into the relation between democracy and economic well-being for this course.

This week’s assignment is to submit a blog entry in which I describe 1) the sample, 2) the data collection procedure, and 3) a measures section describing your variables and how I managed them to address my research question.  So without further ado…

About my Data

Sample

The sample is from the GapMinder project. The GapMinder project collects country-level time series data on health, wealth and development.  The data set for this class only has one year of data for 213 countries.

Data Collection Procedure

Data were collected by a handful of sources, including the Institute for Health Metrics and Evaluation, US Census Bureau’s International Database, United Nations Statistics Division, and the World Bank.

Measures

Income per person (economic well-being) is the 2010 Gross Domestic Product per capita is measured in constant 2000 U.S. dollars.  This allows for comparison across countries with different costs of living.  This data originally came from the World Bank’s Work Development Indicators.

The level of democracy is measured by the 2009 polity score developed by the Polity IV Project.  This value ranges from -10 (autocracy) to 10 (full democracy).  For my analysis this measure was binned into 5 categories developed by the Polity IV Project authors.  These categories and their polity scores are:

  1. Full Democracy (polity score = 10)
  2. Democracy (6 to 9)
  3. Open Anocracy (1 to 5)
  4. Closed Anocracy (-5 to 0)
  5. Autocracy (-10 to -6)

The urbanization rate is measured by the share of the 2008 population living in an urban setting.  This data was originally produced by the World Bank.  The urban population is defined by national statistical offices.  This variable is a possible confounded and will be binned into three categories:

  1. Not Urban (0% to 32% urbanization rate)
  2. In Transition (33%  to 65% urbanization rate)
  3. Urban (< 66% urbanization rate)
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