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.
Brittany Chase / William Paterson University of New Jersey median real estate price is $575,165, which is more expensive than 53.3% of the neighborhoods in New Jersey and 72.5% of the neighborhoods in the U.S.
The average rental price in Brittany Chase / William Paterson University of New Jersey is currently $3,711, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 75.0% of the neighborhoods in New Jersey.
Brittany Chase / William Paterson University of New Jersey is a suburban neighborhood (based on population density) located in Wayne, New Jersey.
Brittany Chase / William Paterson University of New Jersey real estate is primarily made up of small (studio to two bedroom) to medium sized (three or four bedroom) townhomes and apartment complexes/high-rise apartments. Most of the residential real estate is occupied by a mixture of owners and renters. Many of the residences in the Brittany Chase / William Paterson University of New Jersey neighborhood are established but not old, having been built between 1970 and 1999. A number of residences were also built between 1940 and 1969.
Real estate vacancies in Brittany Chase / William Paterson University of New Jersey are 3.9%, which is lower than one will find in 74.0% of American neighborhoods. Demand for real estate in Brittany Chase / William Paterson University of New Jersey is above average for the U.S., and may signal some demand for either price increases or new construction of residential product for this neighborhood.
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 Wayne, the Brittany Chase / William Paterson University of New Jersey neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
People
In a nation where 1 out of every 4 children lives in poverty, the Brittany Chase / William Paterson University of New Jersey neighborhood stands out as being ranked among the lowest 0.0% of neighborhoods affected by this global issue.
In addition, neighborhoodScout's analysis shows that the Brittany Chase / William Paterson University of New Jersey neighborhood has a greater concentration of residents currently enrolled in college than 98.3% of the neighborhoods in the U.S. With 27.1% of the population here attending college, this is very much a college-focused neighborhood.
Also, if you're planning where to retire, the Brittany Chase / William Paterson University of New Jersey neighborhood in Wayne is a great option to consider. According to NeighborhoodScout's exclusive retirement dream area analysis, it's peaceful and quiet, has above average safety ratings compared to other neighborhoods in NJ, offers a wide range of housing options, and has already attracted an enviable mix of college educated seniors. This neighborhood ranks as better for retirement living than 86.3% of the neighborhoods in New Jersey. If you are considering retiring to New Jersey, this is a good neighborhood to look at.
Real Estate
If you love row houses and attached homes, you will probably really like the Brittany Chase / William Paterson University of New Jersey neighborhood. The ambiance, the charm, of row houses is something special. And in sheer abundance of row houses, this neighborhood truly stands out. The real estate here has a higher proportion of row houses and attached homes than nearly any neighborhood in America. In fact, 40.0% of the residential real estate here is classified as row houses and attached homes.
Modes of Transportation
More people in Brittany Chase / William Paterson University of New Jersey choose to walk to work each day (14.7%) than almost any neighborhood in America. If you are attracted to the idea of being able to walk to work, this neighborhood could be a good choice.
Diversity
Did you know that the Brittany Chase / William Paterson University of New Jersey neighborhood has more Arab and Italian ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 6.3% of this neighborhood's residents have Arab ancestry and 16.9% have Italian ancestry.
Brittany Chase / William Paterson University of New Jersey is also pretty special linguistically. Significantly, 2.4% of its residents five years old and above primarily speak Russian at home. While this may seem like a small percentage, it is higher than 98.9% of the neighborhoods in America.
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 Brittany Chase / William Paterson University of New Jersey neighborhood in Wayne are upper-middle income, making it an above average income neighborhood. NeighborhoodScout's exclusive analysis reveals that this neighborhood has a higher income than 82.8% of the neighborhoods in America. In addition, 0.0% of the children seventeen and under living in this neighborhood are living below the federal poverty line, which is a lower rate of childhood poverty than is found in 100.0% of America's neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the Brittany Chase / William Paterson University of New Jersey neighborhood, 47.9% 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 30.6% of the residents employed. Other residents here are employed in clerical, assistant, and tech support occupations (13.4%), and 8.1% in manufacturing and laborer occupations.
Languages
The languages spoken by people in this neighborhood are diverse. These are tabulated as the languages people preferentially speak when they are at home with their families. The most common language spoken in the Brittany Chase / William Paterson University of New Jersey neighborhood is English, spoken by 66.7% of households. Other important languages spoken here include Spanish, Arabic, Langs. of India and Russian.
Ethnicity / Ancestry
Culture is the shared learned behavior of peoples. Undeniably, different ethnicities and ancestries have different cultural traditions, and as a result, neighborhoods with concentrations of residents of one or another ethnicities or ancestries will express those cultures. It is what makes the North End in Boston so fun to visit for the Italian restaurants, bakeries, culture, and charm, and similarly, why people enjoy visiting Chinatown in San Francisco.
In the Brittany Chase / William Paterson University of New Jersey neighborhood in Wayne, NJ, residents most commonly identify their ethnicity or ancestry as Italian (16.9%). There are also a number of people of Asian ancestry (15.8%), and residents who report Irish roots (7.2%), and some of the residents are also of Arab ancestry (6.3%), along with some South American ancestry residents (5.5%), among others. In addition, 26.3% of the residents of this neighborhood were born in another country.
Getting to Work
Even if your neighborhood is walkable, you may still have to drive to your place of work. Some neighborhoods are located where many can get to work in just a few minutes, while others are located such that most residents have a long and arduous commute. The greatest number of commuters in Brittany Chase / William Paterson University of New Jersey neighborhood spend between 15 and 30 minutes commuting one-way to work (35.9% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (56.4%) drive alone in a private automobile to get to work. In addition, quite a number also hop out the door and walk to work to get to work (14.7%) and 8.5% of residents also carpool with coworkers, friends, or neighbors for their daily commute. 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.
