Square Footage of a House and Its Value

A Comparative Analysis of Real Estate Markets in the East North Central Region

Introduction

The real estate market is an essential component of the overall economy, impacting various sectors such as construction, finance, and consumer spending. Understanding regional real estate market dynamics can provide valuable insights for investors, homeowners, and policymakers. This report focuses on analyzing real estate data from the East North Central region of the United States, comprising the states of Illinois, Indiana, Michigan, Ohio, and Wisconsin.

Representative Data Sample

Region

State

County

listing price

$'s per square foot

square feet

random

East North Central

in

grant

East North Central

il

vermilion

East North Central

in

henry

East North Central

in

wayne

East North Central

il

coles

East North Central

il

macoupin

East North Central

in

vigo

East North Central

oh

jefferson

East North Central

il

jackson

East North Central

oh

marion

East North Central

mi

bay

East North Central

il

whiteside

East North Central

oh

trumbull

East North Central

in

madison

East North Central

il

knox

East North Central

il

stephenson

East North Central

il

macon

East North Central

in

delaware

East North Central

il

henry

East North Central

oh

seneca

East North Central

oh

darke

East North Central

oh

scioto

East North Central

oh

belmont

East North Central

oh

sandusky

East North Central

il

rock island

East North Central

oh

clark

East North Central

oh

columbiana

East North Central

in

howard

East North Central

oh

richland

East North Central

il

peoria

Data Analysis

Mean Listing Price: $215,563.33

Median Listing Price: $214,850

Standard Deviation Listing Price: $40,461.10

Mean Square Feet: 1,637.57

Median Square Feet: 1,645.5

Standard Deviation Square Feet: 242.34

Regional samples can sometimes differ significantly from the national market due to specific local factors such as job growth, economic conditions, and demographics. For example, some regions may have higher demand for housing due to a booming local economy, while others may struggle with high unemployment rates or population decline.

The types of housing available in a region can also affect its real estate market. Some regions may have a higher proportion of single-family homes, while others may have more apartments or condominiums. This can lead to differences in average listing prices, price per square foot, and square footage compared to the national market.

Local markets can experience unique trends that may not be present at the national level. For example, a particular region may be experiencing a surge in demand due to new industries moving in or an influx of residents from other parts of the country. This can lead to a regional market that is growing faster or slower than the national market.

The sample consists of 30 data points, which might not be enough to make comprehensive conclusions about the national market. A larger sample size, including more diverse regions, might be needed to draw more accurate comparisons.

I used Simple Random Sampling, which is the most basic method to ensure a random sample. I did this by assigning a unique number to each element in the population and using a random number generator in Excel to select the required sample size. This method ensures that each element in the population has an equal chance of being selected.