If the discrete variable has many levels, then it may be best to treat it as a continuous variable. If you have a discrete variable and you want to include it in a Regression or ANOVA model, you can decide whether to treat it as a continuous predictor (covariate) or categorical predictor (factor). For example, the length of a part or the date and time a payment is received. A continuous variable can be numeric or date/time. Continuous variable Continuous variables are numeric variables that have an infinite number of values between any two values. For example, the number of customer complaints or the number of flaws or defects. Discrete variable Discrete variables are numeric variables that have a countable number of values between any two values. For example, categorical predictors include gender, material type, and payment method. Categorical data might not have a logical order. Categorical variable Categorical variables contain a finite number of categories or distinct groups. Quantitative variables can be classified as discrete or continuous.
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