Discrete and continuous variables Note: Interval data can be recoded into The four types of measurement sca categorical data which have two or more above can be grouped into two bro categories. Be careful that you do not categories, discrete and continuous recode interval data into categories which Discrete variables are those that are make them lose their meaning or become measured on a nominal or ordinal scale less useful in the analysis They classify persons, objects or events according to the quality of their attributes Discrete variables are often called categorical variables Discrete and continuous If you have a mixture of different types of variables data, you may have to record interval data into categorical data in order to use certain Continuous variables are those that are atistical procedures which require data to measured on an interval or ratio scale be categorical. However, there are some They classify persons, objects or events procedures that will work with a mixture of according to the magnitude or quantity of numeric and categorical data. You have to their attributer decide what procedures are appropriate for your analysis, based on the topic of your study, the type of data you are analysing and whether the meaning of the data will be affected by recoding13 25 Discrete and continuous variables • The four types of measurement scales above can be grouped into two broader categories, discrete and continuous. • Discrete variables are those that are measured on a nominal or ordinal scale. They classify persons, objects or events according to the quality of their attributes. Discrete variables are often called categorical variables. 26 Discrete and continuous variables • Continuous variables are those that are measured on an interval or ratio scale. They classify persons, objects or events according to the magnitude or quantity of their attributes. 14 27 • Note: Interval data can be recoded into categorical data which have two or more categories. Be careful that you do not recode interval data into categories which make them lose their meaning or become less useful in the analysis. 28 • If you have a mixture of different types of data, you may have to record interval data into categorical data in order to use certain statistical procedures which require data to be categorical. However, there are some procedures that will work with a mixture of numeric and categorical data. You have to decide what procedures are appropriate for your analysis, based on the topic of your study, the type of data you are analysing and whether the meaning of the data will be affected by recoding