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Chat with our AI personalities
Interval Data: Temperature, Dates (data that has has an arbitrary zero) Ratio Data: Height, Weight, Age, Length (data that has an absolute zero) Nominal Data: Male, Female, Race, Political Party (categorical data that cannot be ranked) Ordinal Data: Degree of Satisfaction at Restaurant (data that can be ranked)
There is no point in collecting data simply for the sake of collecting data. You need to analyse it: summarise it and use key information from it to make some assessments about the data.
Ordinal data is data that can be ranked, but you can not say anything about how far apart the data entries are. You can count and order it but not measure difference between data entries. For example if we talk about teams, one can be first, the next second etc, but that tells us nothing about how far ahead team 1 is. In many surveys they use agree or disagree and you rank your answer from 1 to 5.
Yes. In the field of "ordered statistics" it makes no difference if data is ranked smallest to highest or vice-versa, but the convention is to consider rank = 1 the smallest value and rank = m the largest value of m values.
You need to indicate the conditions.