Methodology

How We Assigned Grades and Ranks

How did Philadelphia get an A- in Population, while San Francisco got a C? To determine grades, we scored each indicator (i.e. each data category, such as change in population or infant mortality rate) within a category using the same formula, so that we could equitably compare all of the indicators to each other.

We used the following formula to score each indicator:

(City X Value – Lowest City Value) = City X Score
(Range of Values)

where

City X Value = indicator value of city being scored
Lowest City Value = lowest indicator value in the data set
Range of Values = difference between the highest and lowest indicator values in the data set
Score = the higher the number, the better

Note: This formula is used when high values are ‘positive’ while low values are ‘negative’ (e.g.
the percent of residents with a high-school diploma). When high values are ‘negative’ (e.g. infant
mortality rates), the following formula was used to score the indicator value:

1- (City X Value – Lowest City Value) = City X Score
(Range of Values)

We applied this formula to every city. Then, we added up all the indicator scores within a category (Population, Health, Education, Community) for each city. For example, the Community score was the sum of the scores of percent of kids in poverty, percent of growth in urbanized land, rate of violent crimes, and recycling. This total score was given a grade using a normal distribution curve.

How We Did The Scores

Cities’ final ranks are based on their total scores. The city with the highest score ranked first, the city with the second-highest score ranked second, and so on. All scoring and grading was done separately for the two city groups—Major and Large cities.

Example: In order to determine the infant mortality rate score for Montgomery, Alabama (Large City with an infant mortality rate of 9.1 deaths per every 1,000 live births), the first step is to find the Large City with the lowest value—in our case, Austin, Texas, at a rate of 4.2. Next, find the Large City with the highest value—this is Richmond, Virginia at a rate of 18.5. Finally, use the formula to determine Montgomery’s score:

1-(9.1 – 4.2) = 0.66
(18.5 – 4.2)

This indicates that Montgomery’s infant mortality rate was slightly better than the infant mortality rate of the majority of the other Large Cities that we studied. Austin gets the highest score of 1, Richmond gets the lowest score of 0, and all the other cities fall somewhere in between.