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What else can I help you with?
What is ordinal statistics?
Ordinal statistics or data is classified as ordinal if the values can be rated on a scale or put i order. Ordinal data can be counted but never measured.
Is asking your birth year a ordinal data?
No, but the answers provide ordinal data.
What are the advantages and disadvantages transforming of continuous data into either discrete or ordinal data?
1.) Discrete: restricted to integers; ordinal subjective
Why is ANOVA used for interval and ratio level data only and not used for nominal or ordinal level data?
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.
Are eye colors ordinal data?
no, they are categorical
IS GPA nominal data or ordinal?
It is ordinal.
What is ordinal statistics?
Ordinal statistics or data is classified as ordinal if the values can be rated on a scale or put i order. Ordinal data can be counted but never measured.
Is asking your birth year a ordinal data?
No, but the answers provide ordinal data.
Should The mean or median be used in ordinal data?
The median is used when reporting ordinal data.
What are the advantages and disadvantages transforming of continuous data into either discrete or ordinal data?
1.) Discrete: restricted to integers; ordinal subjective
True or false Data at the ordinal level are quantitative only?
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.
Why is ANOVA used for interval and ratio level data only and not used for nominal or ordinal level data?
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.
How do you convert ordered data to nominal data?
I think you mean ordinal data. Similar to the golf tournament, you need to determine where to "cut" (from the ordinal data) so as to divide the data into different categories (to the nominal data). For example, if the ordinal data range from 1 to 6 (where 1 = the best) and the cut is 3, then you convert all the numbers from 1 to 3 to "1" (which represents "good") and the all numbers from 4 to 6 to "2" (which represents "bad"). In other words, 1, 2, and 3 from the original ordinal data set are converted to "1" (ordinal data); whereas 4, 5, and 6 from the original date set now become "2" (ordinal data). Eddie T.C. Lam
What is Data that is ranked but not with even intervals?
ordinal
Are eye colors ordinal data?
no, they are categorical
Major advantage of ordinal data over nominal data?
its sick blad
What is the measure of central tendency for nominal and ordinal data?
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.
