Ordinal data has an inherent order, i.e. ranking, in its possible values. For example 'poor, fair, good, excellent' is ordinal becaused there is an assumption that the four possible values are higher from one to the next. It can be coded as 1,2,3,4 but there is no assumption of equal spacing. Nominal data has no inherent ranking, only labeling-e.g. 'apple, strawberry, orange'. The choices are three levels with no assumed value. Any numerical coding does not reflect any quantitative meaning.
Georgette Asherman, Direct Effects, LLC
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ANOVA (Analysis of Variance) is used for interval and ratio level data because it relies on the assumption that the data is continuous and normally distributed, allowing for meaningful calculations of means and variances. Nominal and ordinal data do not meet these criteria; nominal data consists of categorical variables without a numerical relationship, while ordinal data has a ranked order but does not provide equal intervals between ranks. Consequently, ANOVA is not appropriate for these data types as it cannot accurately assess differences in means or variances.
Neither, age is at a ratio level of measurement.
illustrate how you can express the age of group of persons as {1}nominal,{2}ordinal data,{3} interval data,{4}ratio data
Bar charts are used to summarise nominal or ordinal data.
It is ordinal.
Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.
Occupation is nominal data. There is not an order to the category occupation, so that eliminates ordinal and interval.
Education should be treated as a nominal scale because the years spent between two grades are not same for all the grades. i.e. difference between Jr. College and Sr. College isn't same as between graduation and post-graduation.
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ratio
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.
Age is none of the items listed. Age is ratio data.
False. Data at the ordinal level can be either quantitative or qualitative. In ordinal data, the categories have a meaningful order or rank, but the difference between the categories is not necessarily equal.
Kruskal-Wallis H test.
Neither, age is at a ratio level of measurement.
illustrate how you can express the age of group of persons as {1}nominal,{2}ordinal data,{3} interval data,{4}ratio data