Chapter 4: Analysing the Data |

## DichotomisationAs discussed in Chapter 1, variables can be classified in many ways. One way is continuous or discrete. A continuous variable (e.g., length or IQ) takes on many values, it is not restricted to just a few values such as gender (takes two values) or days of the week (takes on seven values). A variable that takes on only two values is A continuous variable is said to contain more information about a construct because it measures it more accurately or more sensitively. Asking a person if they Agree or Disagree to a question does not give as much information about that personŐs level of agreement as does a seven point (Likert) scale
So, in general, you should use continuous variables wherever possible. However, there are times when only dichotomous measures are possible. There are also times when dichotomous variables are useful in their own right. This is mainly when you are only interested in broad comparisons. To compare two or three or four broad groupings can sometimes lead to a clearer understanding of relationships in data than considering continuous data. It is possible to convert continuous measurements to smaller numbers of categories by |

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