If you want a different number of decimals for a particular column, then select Column in the Format menu 

and enter the new number of decimals.  In this dialog box you can also specify a different width for the 

column.  You can also specify that particular columns only contain text data (option  Text format ). The 

latter option is particularly useful when the column contains text data that should not be interpreted as a 

number, e.g. dates: 05/07/1956 must be displayed as such, not as 0.0003652 

A variable may either be categorical or numerical.  Categorical variables may either consist of numeric or 

alphanumeric (string) data.  A numerical variable always consists of numerical data. 

Categorical or qualitative variable 

Categorical or qualitative data may either be entered as numbers or as text strings.  A text string consists 

of one or more alphanumeric characters, placed in quotation marks.  The program will consider every 

expression that cannot be interpreted as a number to be a string, even if it is not placed between quotation 

marks, e.g.  Green , yellow,  10 .  Distinction can be made between Nominal and Ordinal data: 

Nominal data  :  a classification without obvious order, e.g. blood group, male/female. 

Ordinal data  :  ordered categorical data, e.g. endometriosis stage, varicocele grade. 

A variable that can only have 2 values is also called a dichotomous variable, for example pregnant/not 

pregnant, male/female. 

In MedCalc, it is often useful to code categorical data with numerical values: 0 and 1, or 1 2 3 4, etc. 

Numerical or quantitative variable 

A numerical variable consists of numbers, for example 0, 25 or 3.258, or expressions that can be 

interpreted as a number, e.g. LOG(25) or SQRT(VAR1) where VAR1 is a variable's name containing 

numerical data.   

Numerical data may either be continuous or discrete. 

Continuous data  : numbers that can theoretically assume any value between two given values; usually 

measurements, for example: the height of a person. 

Discrete data 

:  data  that  are not continuous (and may have a limited number of values), usually 

counts, for example: the number of children in a family. 

You can easily convert a numerical variable into a categorical variable using the CATEGORISE function 

(see p. 162) or IF function (see p. 163). 

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