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  • U.S. unemployment level - seasonally adjusted monthly number July 2018

Monthly number of unemployed persons in the U.S. from July 2017 to July 2018 (in millions, adjusted)

U.S. unemployment level - seasonally adjusted monthly number July 2018 This statistic displays the seasonally adjusted unemployment level in the USA on a monthly basis. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends. The national unemployment level stood at about 6.28 million unemployed persons in July 2018.
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Number in millions
Jul '176.98
Aug '177.13
Sep '176.76
Oct '176.52
Nov '176.62
Dec '176.58
Jan '186.68
Feb '186.71
Mar '186.59
Apr '186.35
May '186.07
Jun '186.56
Jul '186.28
Number in millions
Jul '176.98
Aug '177.13
Sep '176.76
Oct '176.52
Nov '176.62
Dec '176.58
Jan '186.68
Feb '186.71
Mar '186.59
Apr '186.35
May '186.07
Jun '186.56
Jul '186.28
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Description Source More information
This statistic displays the seasonally adjusted unemployment level in the USA on a monthly basis. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends. The national unemployment level stood at about 6.28 million unemployed persons in July 2018.
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Release date
August 2018
Region
United States
Survey time period
July 2017 to July 2018
Age group
16 years and older
Supplementary notes
Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends. It is normal to report un-adjusted data for current unemployment rates, as these reflect the actual current situation. Seasonally adjusted data may be used for the longer term comparison. Unlike the trend and cyclical components, seasonal components, theoretically, happen with similar magnitude during the same time period each year. The seasonal component of a series are often considered to be uninteresting in their own right and to cause the interpretation of a series to be ambiguous. By removing the seasonal component, it is easier to focus on other components.

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