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.
"sixteenth" is an ordinal number. There is no ordinal number for an ordinal number!
The ordinal number of 43 is 43rd and the ordinal word is forty-third.
The ordinal number of 22 is 22nd and the ordinal word is twenty-second.
the ordinal word for 60 is sixtieth or 60th
Where the form is ordinal.
median
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
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.
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.
. Cardinal Approach refers that you can calculate or Measure the utility (degree of satisfaction) Numerically, while According to ordinal approach you can not measure the utility numerically. 2. Cardinal Approach follow the Law of Diminishing Marginal Utility while Ordinal Approach follow the Indifference Curve. 3.Cardinal Approach Emphasis on units while ordinal approach is based on rank.
A difference is that with ordinal utility approaches, you cannot numerically measure the level of consumer satisfaction. With cardinal utility approaches, you can to an extent.
"sixteenth" is an ordinal number. There is no ordinal number for an ordinal number!
1. Cardinal Approach refers that you can calculate or Measure the utility (degree of satisfaction) Numerically, while According to ordinal approach you can not measure the utility numerically. 2. Cardinal Approach follow the Law of Diminishing Marginal Utility while Ordinal Approach follow the Indifference Curve. 3.Cardinal Approach Emphasis on units while ordinal approach is based on rank. BY SUMIT SONI(IITTM)
The ordinal word is sixtieth. There is no ordinal number.
Chi Square
It depends on the particular set of numbers. Which is closest to the majority of the numbers.If all are random or completely Different numbers maybe the median?If they are really different, median is the best.If they are close to the same, the mode is better.There is no measurement better than the other, unless the data contains outliers.Mean is the most common, but if the data set contains outliers then consider using median or mode.In ADDITON:Which is better between mean, median and mode also depends on which type of data are we considering. There are basically 3 kinds of data:Nominal Data (qualitative data). For eg, marital status can be married, single, divorced or de facto.Ordinal data = the data are actually ranked, for eg Google is the number 1 search engine and yahoo is the no 2 search engine.Interval (numerical): for example: age, height, length, breadth etc.If we are looking at an interval(numerical) data, we can use any mean, median or mode. Mean is generally the best measure for statistical interference if there are no extreme values. When there are extreme values it is better to use median. Mode is very rarely used.If we are looking at nominal data, we cannot calculate mean. Like in the given example, marital status can be married, single, divorced or de facto. Now look at the following tableStatus FrequencyMarried 40Single 60Divorced 20De facto 10In this case we have to choose mode. The same is applicable for shoe size, waist size etc.If we are looking for an ordinal data, where data are ranked, the best measure of central tendency will be median.Apart from the type of data, nature of investigation in hand also affects which measure should be choose. In such cases, a personal judgment should be applied. An example is, if we are tying to compare how good a class did, in comparison with other classes, the best measure of central tendency would be mean. however, if we are looking inside a class and trying to compare how well we did in our class, median would be the best measure of central tendency. Unless the data is nominal, it is very rare that mode is the best measure of central tendency.
The ordinal number of 43 is 43rd and the ordinal word is forty-third.