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.

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Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

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)

No transform

1.07

Box-cox

1.07

Log_b(x-a)

1.07

sqrt(x+a)

1.07

exp(x)

4.27

arcsinh(x)

1.07

Yeo-Johnson

1.07

OrderNorm

0.67

Auto Correlation Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

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