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.
Mountain Creek / Lakeland Heights median real estate price is $297,141, which is more expensive than 53.1% of the neighborhoods in Texas and 38.0% of the neighborhoods in the U.S.
The average rental price in Mountain Creek / Lakeland Heights is currently $2,694, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 87.8% of the neighborhoods in Texas.
Mountain Creek / Lakeland Heights is a suburban neighborhood (based on population density) located in Grand Prairie, Texas.
Mountain Creek / Lakeland Heights real estate is primarily made up of medium sized (three or four bedroom) to large (four, five or more bedroom) single-family homes and mobile homes. Most of the residential real estate is owner occupied. Many of the residences in the Mountain Creek / Lakeland Heights neighborhood are newer, built in 2000 or more recently. A number of residences were also built between 1970 and 1999.
In Mountain Creek / Lakeland Heights, the current vacancy rate is 2.0%, which is a lower rate of vacancies than 86.3% of all neighborhoods in the U.S. This means that the housing supply in Mountain Creek / Lakeland Heights is very tight compared to the demand for property here.
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 Grand Prairie, the Mountain Creek / Lakeland Heights neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
People
One of the really interesting characteristics about the Mountain Creek / Lakeland Heights neighborhood is that, according to NeighborhoodScout's exclusive research, it is an excellent choice in which to reside for college students. Due to its popularity among college students who already choose to live here, its walkability, and its above average safety from crime, the neighborhood is ideal for prospective or already-enrolled college students. Between semesters and during school breaks, you'll notice that the excitement here fluctuates with the college seasons. Despite the excitement however, parents of college-age children can rest easy knowing that this neighborhood has an above average safety rating. For each of these reasons, the neighborhood is rated among the top 4.3% of college-friendly places to live in the state of Texas.
Diversity
Did you know that the Mountain Creek / Lakeland Heights neighborhood has more Mexican ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 66.9% of this neighborhood's residents have Mexican ancestry.
Mountain Creek / Lakeland Heights is also pretty special linguistically. Significantly, 67.7% of its residents five years old and above primarily speak Spanish at home. This is a higher percentage than 97.1% of all U.S. neighborhoods.
The Neighbors
There are two complementary measures for understanding the income of a neighborhood's residents: the average and the extremes. While a neighborhood may be relatively wealthy overall, it is equally important to understand the rate of people - particularly children - who are living at or below the federal poverty line, which is extremely low income. Some neighborhoods with a lower average income may actually have a lower childhood poverty rate than another with a higher average income, and this helps us understand the conditions and character of a neighborhood.
The neighbors in the Mountain Creek / Lakeland Heights neighborhood in Grand Prairie are middle-income, making it a moderate income neighborhood. NeighborhoodScout's exclusive analysis reveals that this neighborhood has a higher income than 44.8% of the neighborhoods in America. With 13.7% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 57.5% of U.S. neighborhoods.
What we choose to do for a living reflects who we are. Each neighborhood has a different mix of occupations represented, and together these tell you about the neighborhood and help you understand if this neighborhood may fit your lifestyle.
In the Mountain Creek / Lakeland Heights neighborhood, 32.3% of the working population is employed in manufacturing and laborer 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 29.5% of the residents employed. Other residents here are employed in executive, management, and professional occupations (26.0%), and 12.2% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the Mountain Creek / Lakeland Heights neighborhood is Spanish, spoken by 67.7% of households. Some people also speak English (26.0%).
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 Mountain Creek / Lakeland Heights neighborhood in Grand Prairie, TX, residents most commonly identify their ethnicity or ancestry as Mexican (66.9%). There are also a number of people of Asian ancestry (6.1%), and residents who report English roots (3.2%), and some of the residents are also of Sub-Saharan African ancestry (2.7%), along with some German ancestry residents (2.2%), among others. In addition, 39.2% of the residents of this neighborhood were born in another country.
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 Mountain Creek / Lakeland Heights neighborhood spend between 15 and 30 minutes commuting one-way to work (43.5% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (73.4%) 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 (16.1%) . 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.
