Abstract
The City of Flint, Michigan, USA has experienced extreme population and economic variability in the past one hundred and fifty years. The City of Flint developed three comprehensive or master plans in order to assess available data, make projections and propose recommendations. The ways in which each plan proved to contain accuracies and failures is instructive for the practices of historical statistical methods and urban planning, particularly as it relates to spatial data. The three plans will be considered in three main sections: planning for population growth (1920), planning for regional rationalization (1960), and planning for a flexible future (2013). Population projections, residential density patterns, and economic and employment data will be reviewed and compared against the planning recommendations and realities. The relationship between statistics and spatial analysis is examined. Discussion is included on ways data and statistical analysis can be utilized for public decision-making and assist with governing.
© 2015 by De Gruyter
Articles in the same Issue
- Frontmatter
- Proceedings of Flint International Statistics Conference Kettering University, June 24–28, 2014
- Urban Planning for Change: Data and Projections in City of Flint Master Plans (1920, 1960 & 2013)
- More Equal and Poorer, or Richer but More Unequal?
- How We Can Evaluate the Inequality in Flint
- Comparing Data Envelopment Analysis and Human Decision Making Unit Rankings: A Survey Approach
- Discrete Pareto Distributions
- Leverage Effect for Volatility with Generalized Laplace Error
Articles in the same Issue
- Frontmatter
- Proceedings of Flint International Statistics Conference Kettering University, June 24–28, 2014
- Urban Planning for Change: Data and Projections in City of Flint Master Plans (1920, 1960 & 2013)
- More Equal and Poorer, or Richer but More Unequal?
- How We Can Evaluate the Inequality in Flint
- Comparing Data Envelopment Analysis and Human Decision Making Unit Rankings: A Survey Approach
- Discrete Pareto Distributions
- Leverage Effect for Volatility with Generalized Laplace Error