Not in Labor Force - Want a Job Now, Marginally Attached, Discouraged Workers
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Not in Labor Force - Want a Job Now, Marginally Attached, Discouraged Workers
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
Board of Governors of the Federal Reserve
Release:
Current Population Survey
Units:
Thousands of Persons
Frequency:
Monthly
Available Through:
06/30/2025
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Order Norm transformation, provides the best normality, the Boxcox variable will also perform well.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Sum.
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 -0.38
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.50 p-value = 0.01 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.93 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 0.75 indicates the data are moderately skewed.
Hartigan's dip test score of 0.03 with a p-value of 0.68 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
Citation:
https://fred.stlouisfed.org/seriesBeta/LNU05026645