The mean cannot be used with ordinal data. The best measure of central tendency for ordinal data is usually the median. A common example of ordinal data is the scale you see in many surveys. 1=Strongly disagree; 2=Disagree; 3=Neutral; 4=Agree; 5=Strongly agree. The mean would have not meaning here ( no pun intended) The median is simple the middle value. The mode does have meaning.
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.
"sixteenth" is an ordinal number. There is no ordinal number for an ordinal number!
· Dependent variable ( student's academic achievement ) : It depend on the way that we use it to write the score (if we write it as a letter it will be an ordinal ,but if we write it as number it will be an interval). · Independent variable ( intelligent ) : Interval, · Independent variable ( attention ) : Interval,
median
The mean cannot be used with ordinal data. The best measure of central tendency for ordinal data is usually the median. A common example of ordinal data is the scale you see in many surveys. 1=Strongly disagree; 2=Disagree; 3=Neutral; 4=Agree; 5=Strongly agree. The mean would have not meaning here ( no pun intended) The median is simple the middle value. The mode does have meaning.
Measurement Scale Best measure of the 'middle' Numerical mode Ordinal Median Interval Symmetrical data- mean skewed data median Ratio Symmetrical data- Mean skewed data median
Nominal
The dependent variable is usually plotted on the "y" or ordinal axis.
No It's continuous variable a that also falls under the category of 'ratio level of measurement'
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.
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.
The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.