R Graphics.

R graphics construction:

I decided to do my use case on the relationship between GDP versus Employment Rate. I was interested to see how strong the correlation if any, was between these two data sets for OECD countries.

I obtained my raw data from http://stats.oecd.org/ and http://en.wikipedia.org/wiki/List_of_OECD_countries_by_GDP_per_capita.

I cleaned this raw data and created two CSV files – GDP.txt and Employment rate.txt.

The first file is Employment rate – this stored each country and it’s employment rate for 2012.

The second file is GDP – this stored each country and it’s Gross Domestic Product for 2012.

I now downloaded the “R” GUI programming interface for windows.

After opening up the “R” programming environment, I created a data frame for each of my CSV files.

gdp <- read.csv(“GDP.txt”, header=T)

ER <- read.csv(“Employment rate.txt”, header=T)

I then merged the above data frames and stored them in a new data frame called “countries”.

countries <- merge(x = gdp, y = ER)

The above created a data frame with 3 columns – Country, GDP and Employment_rate.

When I run print(countries), I obtain the following.

Country              GDP       Employment_Rate

Australia             44407            72.4

Austria                 44141            72.5

Belgium                40838            61.8

Canada                  42114            71.8

Chile                       21486            61.7

CzechRepublic      27527            66.0

Denmark                42787            73.1

Estonia                    24260            66.2

Finland                    39160            69.4

France                      36933            63.8

Germany                  41927            72.7

Greece                       25987            52.3

Hungary                   22635            56.6

Iceland                      39117            78.7

Ireland                      43803            58.7

Israel                         31364            66.0

Italy                           34141            56.9

Japan                         35482            70.4

Korea                         30011            64.2

Luxembourg            89417            64.8

Netherlands             43348            75.3

NewZealand             32888            72.7

Norway                      66135            75.8

Poland                        22782            59.6

Portugal                     25802            62.3

SlovakRepublic        25948            59.8

Slovenia                     28482            64.8

Spain                           32559            56.6

Sweden                       42865            73.7

Switzerland                53641            79.0

Turkey                         18328            48.2

UK                                 35671            69.4

USA                               51689            67.0

I then plotted the GDP column against the Employment_rate column.

Plot(countries$GDP, countries$Employment_Rate)

I then plotted a line showing the positive correlation between Employment Rate and GDP as seen below.

line <- lm(countries$Employment_Rate ~ countries$GDP)

abline(line)

Plot and correlation

I also ran the cor.test function as seen below;

test(countries$GDP, countries$Employment_Rate)

Pearson’s product-moment correlation

data: countries$GDP and countries$Employment_Rate

t = 3.1327, df = 31, p-value = 0.003767

alternative hypothesis: true correlation is not equal to 0

95 percent confidence interval:

1768204 0.7135485

sample estimates:

cor

4903624

As seen from the above results I got a p-value of 0.003767 which imparts a definite correlation.

I obtained a value of 0.49 for the cor value; this imparts a definite positive correlation between the employment rate and GDP.

Information gleamed at a glance.

The information gleamed from the dataset is that there is a definite positive correlation between employment rate and the GDP per Country.

The R graphics proved to be excellent for proving the correlation between GDP and Employment rate.

What other ideas/concepts could be represented via R Graphics.

This could be further expanded to include every country in the world to see would the correlation be similar to the above.

More data sets could be developed to test the correlations between;

IQ and GDP

IQ and Employment rate

Health and GDP

Health and Employment

Education and poverty

The above amongst other concepts/ideas would be very interesting to analyse further using R graphics.

Image of R course completion.

Course completion

 

 

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