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
219,500
$116
1,898
0.380158
East North Central
il
vermilion
254,500
$156
1,632
0.772534
East North Central
in
henry
235,000
$148
1,588
0.297802
East North Central
in
wayne
203,800
$141
1,441
0.246303
East North Central
il
coles
220,800
$117
1,893
0.43187
East North Central
il
macoupin
197,600
$111
1,783
0.577272
East North Central
in
vigo
165,800
$122
1,362
0.887793
East North Central
oh
jefferson
246,500
$136
1,814
0.250615
East North Central
il
jackson
154,300
$105
1,463
0.474863
East North Central
oh
marion
149,700
$116
1,296
0.51351
East North Central
mi
bay
145,100
$117
1,239
0.252858
East North Central
il
whiteside
283,700
$136
2,087
0.823333
East North Central
oh
trumbull
243,000
$133
1,827
0.343069
East North Central
in
madison
229,100
$187
1,224
0.357066
East North Central
il
knox
205,100
$118
1,740
0.807329
East North Central
il
stephenson
235,600
$140
1,682
0.808583
East North Central
il
macon
212,900
$128
1,659
0.681882
East North Central
in
delaware
221,600
$134
1,651
0.943899
East...
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...
…being selected.Scatterplot
The Pattern
The x variable is the sq. footage; the y variable is the listing price. Each variable is useful for making predictions because as the trendline shows, the more sq. footage, the higher the listing price is likely to be.
The association between x and y in the scatterplot is not exactly linear but it is positive. Outliers in the graph do occur and it may be because of the neighborhood the home is in or the condition of the home. In other words, other variables not at play in this plot could be affecting the price.
If I had a 1,800 square foot house, based on the regression equation in the graph, the price I would choose to list at would be $240,000, as this is where the trendline is at that sq.…
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