Visualizing Data using Univariate and Bivariate graphs
This is the last post in the blog posts series for solutions to the weekly assignments in the Data Management and Visualization course offered through Coursera.
This week 4 assignment involves posting the program and the graphs (univariate and bivariate) created using the three variables selected from the dataset (Gapminder), and also providing explanations of the individual variables and the relationship between them.
As earlier stated in previous posts, I selected the ‘oilperperson’, ‘relectricperperson’ and the ‘co2emissions’ from the Gapminder dataset to create univariate and bivariate graphs that will provide answers to the research question:
Is there an association between energy consumption (oil consumed per person and electricity consumed per person) and co2 emissions?
Program and Results (Univariate and Bivariate graphs)
- Oilperperson univariate analysis:
The histogram above shows the distribution of the oilperperson variable which is skewed to the right because most of the countries consume less than 2 tonnes of oil per person.
2. Relectricperperson univariate analysis:
The histogram above shows the distribution of relectricperperson variable which is skewed to the right because there are many countries with lower consumption of electricity per person. Most countries consume electricity less than 2000 kWh per person.
3. Co2emissions univariate analysis:
The histogram above shows the distribution of co2emissions variable which is skewed to the right because most countries emitted carbon dioxide less than 25 billion metric tons.
4. Scatter plot for the Association between oilperperson and co2emissions
The scatter plot above shows that there is a positive association between the oil consumed per person and co2 emitted.
5. Scatter plot for the Association between relectricperperson and co2emissions
The scatter plot shows that there is a positive association between the electricity consumed per person and the c02 emitted.
This is the end of the solution to week 4 assignment for the Data Management and Visualization course.