CPI: Medical Care Commodities in U.S. City Average
Why Use This Data Source In Your Models?
CPI: Medical Care Commodities in U.S. City Average
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Bureau of Labor Statistics
Release:
Consumer Price Index
Units:
Index 1982-1984=100, Not Seasonally Adjusted
Frequency:
Monthly
Available Through:
10/31/2024
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 Weighted Average.
Auto Correlation Analysis:
Data shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.40 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 -0.23 indicates the data are fairly symmetrical.
Hartigan's dip test score of 0.05 with a p-value of 0.00 inidcates the data is multimodal
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:
U.S. Bureau of Labor Statistics, Consumer Price Index for All Urban Consumers: Medical Care Commodities in U.S. City Average [CUSR0000SAM1], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CUSR0000SAM1, May 3, 2024.
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