Answer: Continuous if looking for exact age, discrete if going by number of years. It is also often the case (especially in surveys) that the variable salary (quantitative continuous) is transformed into a qualitative ordinal variable with different range of salaries (e.g., < 1000€, 1000 - 2000€, > 2000€). Therefore the set they come from is infinite. (The fifth friend might count each of her aquarium fish as a … Categorical data might not have a logical order. When working with statistics, it’s important to recognize the different types of data: numerical (discrete and continuous), categorical, and ordinal. However it would be continuous if measured to an exact amount of time passed since the start of something. As I already mentioned, median splits create arbitrary groupings that eliminate all detail. Discrete variable Discrete variables are numeric variables that have a countable number of values … But there are … Same goes for age when age is transformed to a qualitative ordinal variable with levels such as minors, adults and seniors. So when deciding whether to treat a predictor as continuous or categorical, what you are really deciding is how important it is to include the detailed information about the variation of values in the predictor. Likewise, continuous predictors, like age, systolic blood pressure, or percentage of ground cover should be specified as continuous. It is just a factor or categorical variable. I know that isn’t an answer you were considering. Categorical predictors, like treatment group, marital status, or highest educational degree should be specified as categorical. For … For example, categorical predictors include gender, material type, and payment method. Quantitative variables can be classified as discrete or continuous. Yes. Categorical variable Categorical variables contain a finite number of categories or distinct groups. What is an example of a continuous variable? A continuous variable is considered ratio if it has a meaningful zero point (i.e., as in age or distance). On the other hand for instance, If your age is continuous (rather than age brackets) then it would be a covariate. Some examples of variables in statistics might include age, eye color, height, number of siblings, gender, or number of pets. Statistics Organizing and Summarizing Data Categorical Graphs. Data are the actual pieces of information that you collect through your study. 1 Answer S.S Jan 25, 2017 Discrete if measured in a number of years, minutes, seconds. For example, if you ask five of your friends how many pets they own, they might give you the following data: 0, 2, 1, 4, 18. Some other situations also throw away the detail, but in a way that is less arbitrary and that may give you all the … Explanation: Age is measured in units that, if precise enough, could be any number. Predictor variables in statistical models can be treated as either continuous or categorical. But the properties “discrete” and “continuous” are not properties of the concept itself, “age,” they are properties of the methodology you are applying to the concept. Usually, this is a very straightforward decision. As an example, suppose that the random variable X, representing your exact age in years, could take on any value between 0 and 122.449315 (the latter value being the approximate age in years of the oldest … If a data set is continuous, then the associated random variable could take on any value within the range.