Visualizing Life Satisfaction data by Multivariate Analysis

This week OECD relaunched their Better Life Index this week and provided data behind it.

I’ve applied multivariate statistical data analysis methods to average value and you can see results below. Quite interesting groups of countries had emerged.

X-axis separates countries by those with high Life satisfaction index vs those with low. Y axis separates countries by job availability.

  • The most satisfied group of countries is within top right quadrant, having all highly developed countries.
  • The least satisfied group of countries is in the bottom left quadrant of the plot with unemployment being the major factor contributing into their unsatisfaction. This is highest for Eastern European block which experienced economical difficulties in recent years.
  • Countries at top left quadrant are less happy  than  those in the top right quadrant, but not by much. The major factors are high level of crime and long hard working hours. The least satisfied in this group is Turkey (farthest on the plot from Life Satisfaction Index).  Interestingly, Israel has one of the highest wealth and health indicators, lowest crime but at the same time long working hours and worse housing conditions.
  • Countries in the center of the plot is where all indicators balance out. Level of life satisfaction for this group is in between the worse groups. It balanced out by not very high “positive” indicators such as wealth and health and not very high “negative” indicators such as unemployment and crime.
  • Education does not seem to affect life satisfaction as much as other parameters. It is lowest for the group of countries in the left top quadrant and highest for the group in the right top quadrant but both these groups are quite satisfied with life.

Vaccine awareness week:

I have combined the following data into one data matrix:
- 2009 Vaccination data table (subset of most often given vaccines reflecting the trend) ;
 - American Human Development Index by State from American Human development Project;
- Classification of Blue and Red states.

Principal Component Analysis was then applied to this table of data with autoscaling.

PC1 captures 39% of variance in the data and separates samples by those having high rank (cumulative index), high Education, Income and Health index from those having low Rank. Mostly blue states and some red states (AK, ND, NE, UT, KS) have highest rank. Vaccination rates do not contribute into PC1 (close to 0) indicating that there is no direct correlation between human development index and vaccination. PC 2 separates states by vaccination rates. Those on top have higher vaccination rates that those on the bottom of a biplot. There is week correlation (captured in ~16% of variance in the data) between vaccination rates and education and income index and rank. 4 groups of states are classified by PCA: 1. Red states having quite good vaccination rates and very bed HD index. 2. Mostly blue states and some red states having best vaccination rates and best HD index. 3. Purple states having worst vaccination rates and worst HD index. 4. Mixed states - some blue, some red and Co with very bed vaccination rates but high Health Index.
vaccination statistics