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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
In qualitative variables, nominal data involves categories with no inherent order, such as colors or types of fruit. Ordinal data, on the other hand, includes categories that have a meaningful order or ranking, such as education levels or customer satisfaction ratings.
Nominal
No It's continuous variable a that also falls under the category of 'ratio level of measurement'
The dependent variable is usually plotted on the "y" or ordinal axis.
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.
The answer will depend on the nature of the data.If the data are qualitative then the only option is the mode.If they are ordinal then you have a choice between the mode and median. The mode may be a better measure when the data are very skewed. Otherwise the median is usually better.For any higher level of measurement is is also possible to calculate the mean. In such cases the median or mean are better. For very skew distributions the median is better but otherwise is should be the mean.