Data includes measurements on mortality rate and explanatory variables (air-pollution, socio-economic and meteorological) for 60 US cities in 1960. This data was originally published in McDonald, G.C. and Schwing,
R.C. (1973) 'Instabilities of regression estimates relating air pollution
to mortality', Technometrics, vol.15, 463-482. It was redistributed through Carnegie Mellon University's StatLib (lib.stat.cmu.edu). Brief codebook notes that it is heavily used for research in ridge regression.
PhysicalDescription
Form (authority = gmd)
Extent (unit = variables)
16
InternetMediaType
application/vnd.ms-excel
InternetMediaType
text/plain
InternetMediaType
text/csv
TableOfContents
PREC (Average annual precipitation in inches) -- JANT (Average January temperature in degrees F) -- JULT(Average July temperature in degrees F) -- OVR65 (Percentage of 1960 SMSA population aged 65 or older) POPN (Average household size) -- EDUC (Median school years completed by those over 22) -- HOUS (Percentage of housing units which are found and with all facilities) -- DENS (Population per sq. mile in urbanized areas, 1960) -- NONW (Percentage of non-white population in urbanized areas, 1960) -- WWDRK (Percentage employed in white collar occupations) -- POOR (Percentage of families with income <$3000) -- HC (Relative hydrocarbon pollution potential) -- NOX (Relative nitric oxide pollution potential) -- SO@ (Relative sulphur dioxide pollution potential) -- HUMID (Annual average percentage relative humidity at 1 p.m.) -- MORT (Total age-adjusted mortality rate per 100,000)
TargetAudience (authority = Domain)
Cognitive science
TargetAudience (authority = Domain)
Computer science
Note (type = formats available)
Available as Microsoft Excel workbook (xslx); comma separated values (csv) and original plain text.
Note (type = creation/production credits)
Data set was downloaded with permission from the Carnegie Mellon StatLib (http://lib.stat.cmu.edu/datasets/pollution)
Note (type = supplementary materials)
Data set includes original text manifest and a small codebook explaining the 16 variables.
Name (type = personal)
NamePart (type = family)
McDonald
NamePart (type = given)
Gary C.
Role
RoleTerm (authority = marcrelator); (type = text)
Creator
Name (type = personal)
NamePart (type = family)
Schwing
NamePart (type = given)
Richard C.
Role
RoleTerm (authority = marcrelator); (type = text)
Creator
RelatedItem (type = isAssociatedWith)
TitleInfo
Title
Instabilities of Regression Estimates relating Air Pollution to Mortality. Technometrics, v. 15, pp. 463-482 (1973)
Identifier
0040-1706
RelatedItem (type = isAssociatedWith)
TitleInfo
Title
The Independent Sign Bias: Gaining Insight from Multiple Linear Regression / Michael J. Pazzani and Stephen D. Bay
Air Pollution and Mortality for 60 US Cities in 1960
Identifier (type = local)
rucore00000002096
Extension
DescriptiveEvent
Type
Related publication
Label
Article referencing the data set Air Pollution and Mortality for 60 U.S. Cities in 1960
AssociatedObject
Type
Article
Relationship
References
Name
Pazzani, Michael J. and Bay, Stephen D. (1999) The Independent Sign Bias: Gaining Insight from Multiple Linear Regression: Proceedings of the Twenty First Annual Conference of the Cognitive Science Society.
Article referencing the data set, Air Pollution and Mortality for 60 U.S. Cities in 1960
DateTime
1973
Detail
McDonald, G.C. and Schwing, R.C. (1973) "Instabilities of Regression Estimates Relating Air Pollution to Mortality," Technometrics, v. 15, pp. 463-482.
RightsDeclaration (AUTHORITY = RU_Research); (ID = ruRes0001)
Copyright for research resources published in RUcore is retained by the copyright holder. By virtue of its appearance in this open access medium, you are free to use this resource, with proper attribution, in educational and other non-commercial settings. Other uses, such as reproduction or republication, may require the permission of the copyright holder.
Copyright
Status
Copyright protected
Availability
Status
Open
Note
Permission received from the repository of record, Statlib at the Carnegie Mellon University.