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I have a Dataset like this. I would Like to know whether year and origin are either ordinal or nominal variables and why?. I know what are ordinal and nominal variables, my problem is about figuring out these. The last column is Model. The word Model has skipped past to the next line. Sorry about it. Thanks a lot for any suggestions.

> head(x,20)








>             mpg cylinders displacement horsepower weight acceleration year origin 
> model                      
>         1   18         8          307        130   3504         12.0   70      1    chevrolet chevelle malibu
>         2   15         8          350        165   3693         11.5   70      1            buick skylark 320
>         3   18         8          318        150   3436         11.0   70      1           plymouth satellite
>         4   16         8          304        150   3433         12.0   70      1                amc rebel sst
>         5   17         8          302        140   3449         10.5   70      1                  ford torino
>         6   15         8          429        198   4341         10.0   70      1             ford galaxie 500
>         7   14         8          454        220   4354          9.0   70      1             chevrolet impala
>         8   14         8          440        215   4312          8.5   70      1            plymouth fury iii
>         9   14         8          455        225   4425         10.0   70      1             pontiac catalina
>         10  15         8          390        190   3850          8.5   70      1           amc ambassador dpl
>         11  15         8          383        170   3563         10.0   70      1          dodge challenger se
>         12  14         8          340        160   3609          8.0   70      1           plymouth 'cuda 340
>         13  15         8          400        150   3761          9.5   70      1        chevrolet monte carlo
>         14  14         8          455        225   3086         10.0   70      1      buick estate wagon (sw)
>         15  24         4          113         95   2372         15.0   70      3        toyota corona mark ii
>         16  22         6          198         95   2833         15.5   70      1              plymouth duster
>         17  18         6          199         97   2774         15.5   70      1                   amc hornet
>         18  21         6          200         85   2587         16.0   70      1                ford maverick
>         19  27         4           97         88   2130         14.5   70      3                 datsun pl510
>         20  26         4           97         46   1835         20.5   70      2 volkswagen 1131 deluxe sedan
kjetil b halvorsen
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AdeeThyag
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  • I suppose 'Year' is ordinal here (as it usually is). Hard to say just from your Question of what use it is overall, because you show only one year. // I deduce from 'Model' that 'Origin' means _country/region of origin_ (1=US, 2=Germany / EU, 3=Japan / Asia) and so nominal. // Partly, I'm "cheating" because I think I've seen this dataset and analyses of it before. (If so, you show only a fragment.) – BruceET May 16 '18 at 08:01
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    I would argue that the year variable satisfies the criteria for interval measures, as each 1 unit change in year is equal to every other 1 unit change in year. – dbwilson May 16 '18 at 16:29

1 Answers1

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If origin codes, say, country of origin, it is nominal (categorical). As for year, measuring time, it is at least ordinal, but typically how it should be modeled would depend on context.

With very few distinct values, in some cases it might be preferable to treat it as nominal. For a more general discussion see What type of data are dates?

kjetil b halvorsen
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