Homeownership Rate by State
Why Use This Data Source In Your Models?
The homeownership rate provides an indication of the percentage of the population that owns as opposed to rents. This gives an indication of the stability of real estate markets as well as economic stability.
Homeownership Rate by State
Instantly Download this Data Using Our Automated Feature Engineering Tool.
Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Census Bureau
Release:
Housing Vacancies and Homeownership
Units:
Percent, Not Seasonally Adjusted
Frequency:
Annual
Available Through:
12/31/2023
Suggested Treatment:
The data shows seasonality. The data should be adjusted. While the Order Norm transformation, provides the best normality, the Arcsin variable will also perform well.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
Auto Correlation Analysis:
Data does not show strong auto correlation indicating no need for differencing
The ACF indicates 0 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.14 p-value = 0.07 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.86 with a p-value =0.08 indicating the data follows a normal distribution.
A skewness score of -0.03 indicates the data are fairly symmetrical.
Hartigan's dip test score of 0.13 with a p-value of 0.08 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Data Notes:
The following states do not report for this feature: District of Columbia, Puerto Rico. Additionally, 2020 data is not currently available.
Citation:
Varies
Designed For Data Scientists and Analysts
400+ Data Sources
Use our platform to aggregate, normalize, and profile open source and premium control data. Spend less time finding and wrangling data, and more time building efficient and feature-rich machine learning data pipelines.
Data Science Treatments
Instantly apply industry-standard data science treatments and transformations, including (but not limited to) Differencing, Lead/Lag, Box Cox. Easily manipulate data across different time and geographic grains.
Auto Discovery
Our Patent Pending iterative testing engine allows you to upload your target variable, and the platform will test for possible statistical relationships across all available data sources. Saving you time and removing analyst bias.
Data Ingestion
Easily integrate your Ready Signal data to the data science platform of your choice. Connect directly to Ready Signal through our API or using one of our pre-built data connectors or download directly in Excel or CSV format.
