Timeline for Explanation of the different variable types in statistics?
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
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| May 4, 2016 at 3:43 | answer | added | mandata | timeline score: 1 | |
| Jun 23, 2015 at 17:13 | comment | added | grasshopper | @whuber I understand what you are saying, for example the other day I got really confused by a version of Naive Bayes specifically meant for text classification, but at the end of the day aren't these things different data \types eventually broken down into these variable ty]= | |
| Jun 23, 2015 at 15:10 | comment | added | whuber♦ | This question is misguided, I am afraid. It is a mistake to use Stevens' typology to decide whether or not a statistical method can be applied to data. This can--and does--seem to rule out powerful, appropriate methods (such as Poisson regression for continuous responses). It misleads people into thinking that selecting a statistical procedure is merely a matter of figuring out a variable "type." It also has misled many into overlooking the rich, complex variety of data, ranging from counts to differences to proportions to sounds to images and more, that don't fit into this classification. | |
| Jun 23, 2015 at 8:56 | comment | added | Glen_b | Stevens' level of measurement typology is commonly used (and the division in this question is partly based on that one); in that typology discrete numeric variates are either ratio or interval, but in statistics they're generally treated differently from continuous ratio or interval variates. (That typology and the one in your question are also not the only way to divide up variable "types") | |
| Jun 23, 2015 at 7:40 | answer | added | grasshopper | timeline score: 7 | |
| Jun 23, 2015 at 7:25 | comment | added | grasshopper | @DeepNorth I used to think quantitative meant that there was some continuous function with the data but it looks like this only applies to regressive data. | |
| Jun 23, 2015 at 7:13 | comment | added | Deep North | I think there are only two type of variables in statistics (continuous and discrete, or some people may say three, continuous and discrete). Categorical, nominal and ordinal are all discrete, Categorical may include nominal and ordinal, while nominal has no order (or rank), ordinal has some order or (rank). The Quantative and Qualitative classification is really confusing (at least to me). I think Qualitative is also Quantative in statistics. | |
| Jun 23, 2015 at 5:45 | comment | added | Ayalew A. | You could get explanations and examples of the different variable types from any introductory statistics book. Also see this and this links for brief explanations and examples. | |
| Jun 23, 2015 at 4:52 | history | asked | grasshopper | CC BY-SA 3.0 |