choose Track 1: Cost of Living data analysis
Part 1. Analytics
a. Proposed research questions:
Q1: "Analyze the development of cost-of-living over time in London. Are there any detectable trends?" Q2: "How does the cost of living in London compare to other major cities around the world?" Q3: "What are the main factors contributing to the increase in the cost of living in London?"
b. Type of data to answer research questions:
Q1: Historical data on cost of living in London, including housing, transportation, food, and other expenses. Q2: Cost of living data for other major cities globally, including similar categories as for London (housing, transportation, food, etc.). Q3: Data on factors contributing to the cost of living, such as inflation rates, wage growth, population growth, and housing supply in London.
Appropriateness of datasets:
Q1: The provided dataset on the cost of living increase in London is appropriate to answer this question. Q2: The Global Cost of Living Index dataset (example: Numbeo or The Economist Intelligence Unit) would be appropriate for this question. This dataset should include a comprehensive list of cities and their cost of living indices. Q3: Data from the UK Office for National Statistics (ONS) and other relevant sources like the Bank of England could be used to gather information on inflation rates, wage growth, population growth, and housing supply.
c. Correlation between datasets:
The datasets for Q1 and Q2 can be correlated by comparing the cost of living indices across cities, revealing trends and patterns in the cost of living worldwide. The dataset for Q3 can be correlated with the dataset for Q1 to investigate how specific factors contribute to the cost of living increases in London over time. This can help identify key drivers of cost of living changes and potential areas for intervention.
Part 2. Design and Discussion
a. Proposed visualizations:
Line chart: A line chart to represent the development of the cost of living in London over time, with x-axis as time and y-axis as the cost of living index. This will help answer Q1 by showing trends and patterns in the cost of living.
Scatterplot: A scatterplot comparing the cost of living index of London to other major cities worldwide, with x-axis as cities and y-axis as the cost of living index. This visualization will help answer Q2 by providing a clear comparison of the cost of living between London and other major cities.
Stacked bar chart: A stacked bar chart representing the main factors contributing to the increase in the cost of living in London over time, with x-axis as time and y-axis as the cumulative impact of each factor on the cost of living index. Each segment of the bar would represent one of the main factors (inflation rates, wage growth, population growth, and housing supply). This visualization will help answer Q3 by displaying the relative contribution of each factor to the overall cost of living increase.
b. Design rationale for each visualization:
Line chart rationale: A line chart is an effective way to represent continuous data over time, allowing the viewer to easily identify trends and patterns. In this case, it helps to visualize the development of the cost of living index in London and determine if there are any notable changes or periods of stability.
Scatterplot rationale: A scatterplot is a useful visualization for comparing values across multiple categories (in this case, cities). By plotting each city's cost of living index, we can easily identify cities with similar or higher costs of living compared to London, providing context and insight into the global cost of living landscape.
Stacked bar chart rationale: A stacked bar chart allows for the comparison of multiple factors contributing to a single value over time. By using this type of visualization, we can understand the relative importance of different factors in driving the cost of living increase in London. Additionally, this visualization can reveal potential correlations between the factors and the cost of living, informing possible interventions to address these issues.