What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Princeton Heights / University Row median real estate price is $179,636, which is more expensive than 39.4% of the neighborhoods in Ohio and 19.3% of the neighborhoods in the U.S.
The average rental price in Princeton Heights / University Row is currently $1,548, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 67.4% of the neighborhoods in Ohio.
Princeton Heights / University Row is a suburban neighborhood (based on population density) located in Dayton, Ohio.
Princeton Heights / University Row real estate is primarily made up of medium sized (three or four bedroom) to large (four, five or more bedroom) single-family homes and small apartment buildings. Most of the residential real estate is owner occupied. Many of the residences in the Princeton Heights / University Row neighborhood are older, well-established, built between 1940 and 1969. A number of residences were also built before 1940.
Vacant apartments or homes are a major fact of life in Princeton Heights / University Row. The current real estate vacancy rate here is 23.9%. This is higher than the rate of vacancies in 90.9% of all U.S. neighborhoods. In addition, most vacant housing here is vacant year round. This can sometimes be the case in neighborhoods dominated by new construction that is not yet occupied. But often neighborhoods with vacancy rates this high are places that can be plagued by a protracted vacancy problem. If you live here, you may find that a number of buildings in your neighborhood are actually empty.
Notable & Unique Neighborhood Characteristics
Many things matter about a neighborhood, but the first thing most people notice is the way a neighborhood looks and its particular character. For example, one might notice whether the buildings all date from a certain time period or whether shop signs are in multiple languages. This particular neighborhood in Dayton, the Princeton Heights / University Row neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
People
The Princeton Heights / University Row neighborhood has a greater percentage of children living in poverty (61.7%) than found in 97.2% of all U.S. neighborhoods. Children living in poverty is one of the challenges facing America, and the world, and in this neighborhood in particular, the problem can be considered acute.
Diversity
Did you know that the Princeton Heights / University Row neighborhood has more Sub-Saharan African and Haitian ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 14.9% of this neighborhood's residents have Sub-Saharan African ancestry and 2.7% have Haitian ancestry.
The Neighbors
How wealthy a neighborhood is, from very wealthy, to middle income, to low income is very formative with regard to the personality and character of a neighborhood. Equally important is the rate of people, particularly children, who live below the federal poverty line. In some wealthy gated communities, the areas immediately surrounding can have high rates of childhood poverty, which indicates other social issues. NeighborhoodScout's analysis reveals both aspects of income and poverty for this neighborhood.
The neighbors in the Princeton Heights / University Row neighborhood in Dayton are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 70.6% of U.S. neighborhoods. With 61.7% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 97.2% of U.S. neighborhoods.
A neighborhood is far different if it is dominated by enlisted military personnel rather than people who earn their living by farming. It is also different if most of the neighbors are clerical support or managers. What is wonderful is the sheer diversity of neighborhoods, allowing you to find the type that fits your lifestyle and aspirations.
In the Princeton Heights / University Row neighborhood, 53.8% of the working population is employed in executive, management, and professional occupations. The second most important occupational group in this neighborhood is sales and service jobs, from major sales accounts, to working in fast food restaurants, with 17.7% of the residents employed. Other residents here are employed in clerical, assistant, and tech support occupations (15.5%), and 13.0% in manufacturing and laborer occupations.
Languages
The most common language spoken in the Princeton Heights / University Row neighborhood is English, spoken by 96.9% of households.
Ethnicity / Ancestry
Boston's Beacon Hill blue-blood streets, Brooklyn's Orthodox Jewish enclaves, Los Angeles' Persian neighborhoods. Each has its own culture derived primarily from the ancestries and culture of the residents who call these neighborhoods home. Likewise, each neighborhood in America has its own culture – some more unique than others – based on lifestyle, occupations, the types of households – and importantly – on the ethnicities and ancestries of the people who live in the neighborhood. Understanding where people came from, who their grandparents or great-grandparents were, can help you understand how a neighborhood is today.
In the Princeton Heights / University Row neighborhood in Dayton, OH, residents most commonly identify their ethnicity or ancestry as Sub-Saharan African (14.9%). There are also a number of people of English ancestry (8.3%), and residents who report German roots (7.2%), and some of the residents are also of African ancestry (7.0%), along with some Haitian ancestry residents (2.7%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in Princeton Heights / University Row neighborhood spend between 15 and 30 minutes commuting one-way to work (46.5% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (79.6%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (7.8%) . In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
