Knowledge base | Statwing

Variable types like Numbers and Categories, how Statwing treats different variable types differently

Each column of the spreadsheet/table (the “dataset”) is a “variable.” Statwing intelligently interprets the dataset and classifies each variable into a type. The most important variable types are the following:

  • nums-icon-for-wp Numbers: Points on a scale (like weight or dollars) or a count (like number of months as a customer). Some statistical programs call this type “continuous”.
  • cats-icon-for-wp Categories: A grouping (like gender or political party).
  • cats-icon-for-wp Time: Most kinds of time, including years (“2010″), dates (“1/27/1984″), timestamps (“4/7/14 19:08″), times of day (“5:34 AM”), and more. Durations, like “7” seconds or minutes or days, are best classified as Numbers. Statwing automatically guesses whether you’re using MM/DD/YYYY format or DD/MM/YYYY format, based on dates like 31/12/2014 (or 12/31/2014) that indicate which type is being used.
  • ranks-icon-for-wp Ranks: Ordered categories (like military ranks) or rank ordering (like place in a race). If you asked survey respondents to select which annual income bucket they are in (e.g., “$0 to $25k” and “$25k to $50k”) instead of allowing them to respond freely (e.g., “$45,223″ and “$89,400″), those buckets have a clear order and are therefore Ranks. Typically Ranks are initially interpreted by Statwing as Categories; after the data is uploaded, you’ll have to go to Variable Settings and change the variable to Ranks. Your Categories will then be treated more or less as Numbers; for example, “$0 to $25k” becomes 1, “$25k to $50k” becomes “2”, etc.. Some statistical programs call this type “ordinal”.
  • Screen Shot 2014-09-21 at 10.45.01 PM IDs: A column of text where every row is different from every other row, typically a unique ID for this row (e.g., “Respondent1284″). Statwing cannot usefully analyze ID variables.
  • Screen Shot 2014-09-21 at 10.47.41 PM Checkboxes: A group of columns that only have two non-missing values each (for example, “Checked” and “Unchecked”). Learn more about how Statwing handles checkboxes. If Statwing mistakenly groups columns together, you can use variable settings (see below) to ungroup them.
Statwing is occasionally incorrect when it guesses what type of data you have. To correct Statwing’s error go to variable settings, then change that variable’s settings from one type to another (most commonly, changing Numbers to Categories).



Statwing will produce differently structured output for different types of variables, like a histogram when you Describe Numbers...


...but a bar chart when you Describe Categories: