What kinda of Variable is this?

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Discussion Overview

The discussion revolves around the classification of a set of data representing monthly quantities of animal feed ordered by a consumer. Participants explore whether these values can be categorized as "quantitative ratio variables" and discuss the implications of different variable classifications in statistics.

Discussion Character

  • Debate/contested
  • Technical explanation

Main Points Raised

  • One participant questions whether the data can be classified as "quantitative ratio variables," suggesting that the term "ratio" may not be applicable and recommending a review of variable types.
  • Another participant distinguishes between discrete and continuous variables, proposing that the data may represent a continuous distribution limited by measurement precision and rounding.
  • A concern is raised about the mixed levels of precision in the data, with a suggestion that values should be consistently formatted for proper analysis.
  • The original poster expresses a desire to understand the linearity of production based on the data, indicating that the consumer's ordering behavior is constrained within specific limits.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the classification of the variables, with differing opinions on whether they should be considered ratio variables or if another classification is more appropriate. The discussion remains unresolved regarding the best categorization.

Contextual Notes

There are limitations regarding the precision of the data points, as some values are presented with different levels of decimal places, which may affect analysis. The discussion also highlights the variability in terminology used across different statistical texts.

Who May Find This Useful

This discussion may be useful for individuals studying statistics, particularly those interested in variable classification and data analysis methods in practical applications.

nitsuj
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The following values are tonnes of a specific animal feed for a specific consumer.

Jan - 13.97
Feb - 12
Mar - 11
Apr - 5.87
May - 10
Jun - 13.95
Jul - 15.96

Are these variables best described as "quantitative ratio variables" and why?

If not what would be the most accurate class for these variables and why?

I pretty green when it comes to stats :smile:, hopefully this isn't too easy to be worth a reply.
 
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nitsuj said:
Are these variables best described as "quantitative ratio variables" and why?

My personal opinion is that such data isn't obviously a "ratio" of any kind, but you should list all the variable types we have to pick from.

Such classifications of variable types are not standard terminology across all statistics texts. Perhaps you are studying statistics in a specialized field.
 
Mathematically, there are discrete and continuous variables. In applications, variables are sometimes broken down into ordered categorical variables, unordered categorical variables and indicator variables. Since virtually all data are discrete, the question becomes: "What kind of distribution do the data represent?" In your case, I would say that the observations come from a continuous distribution of measure, limited by the precision of measurement and the convenience of rounding. By the this I mean that, in principle, uncountably many possible values lie between the values you actually observed.

EDIT: Your particular data set has some problems in that you have numbers like 10 and others like 13.97. At the very least a value like "10" should be written as 10.00. However, you really can't properly analyze data with data points having such mixed levels of precision.
 
Last edited:
Thanks for the replies guys!

SW Vandecarr,
Thanks for the reply Stephen,

The intent is to try and see if the production is linear enough to assume a feed order will be placed and production could be planned accordingly. i.e. in Jan the customer will likely order 13 tonnes of feed, so in Dec we produce the feed in advance.

Distribution would be what ever is between the high & low. Said different, this is all the data there is. I think that's what you were asking. i.e. the consumer would never order 20 tonnes or 2 tonnes of feed in a month.

Not sure if that helps,

I think I might need to take a course or two in this.
 

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