Median Sales Price of Houses Sold in the US
Why Use This Data Source In Your Models?
Median sales price of houses sold describes supply and demand of housing in the United States, and can predict consumer behavior around purchasing or renting housing.
Median Sales Price of Houses Sold in the US
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Census Bureau
Release:
Housing & Urban Development
Units:
Dollars, Not Seasonally Adjusted
Frequency:
Quarterly
Available Through:
09/30/2024
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Square Root transformation, provides the best normality, the Untransformed 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 shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.04
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.15 p-value = 0.04 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.91 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 0.95 indicates the data are moderately skewed.
Hartigan's dip test score of 0.03 with a p-value of 0.99 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal Impact
Seasonal and Trend Decompostion
Citation:
Board of Governors of the Federal Reserve System (US), Household Debt Service Payments as a Percent of Disposable Personal Income [TDSP], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, December 13, 2019.
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