No It's continuous variable a that also falls under the category of 'ratio level of measurement'
Ordinal
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
Age is none of the items listed. Age is ratio data.
ordinal
Actually, it can be and is frequently treated as either. If the data is collected as a numerical value (for example, $35,500), then it is continuous. However, it is often simpler and more useful, especially in surveys, to collect the data as a set of ranges (20,000 - 29,999; 30,000 - 39,999; etc.). In this case, it would be an ordinal variable. Ordinal variables are discreet categories that still have a rank order.
Ordinal
Ordinal. Though more likely interval or even ratio scale.
ordinal
Nominal and ordinal variables are both qualitative or discrete variables. Nominal variables allow for only qualitative classification while an ordinal variable is a nominal variable, but its different states are ordered in a meaningful sequence.
Nominal
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
The dependent variable is usually plotted on the "y" or ordinal axis.
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
Yes it is. It is an ordinal variable ( which means it is meaningful ) because rank has an order and it is meaningful to rank the soldiers.
Ordinal.
It depends on how the variable is used. At its simplest, it would be a nominal or categorical value but, if used as part of a time series, it would be an ordinal variable.
Depends, if you're looking for the raw score then you have a continuous ordinal variable. If you have range of number of car accidents, then you have an interval variable.