What is the difference between quantitative and categorical data

The data research is most likely low sensitivity, for instance, either good/bad or yes/no.Categorical variables take category or label values and place an individual into one of several groups.There are two types of variables:For example, suppose you have a variable, economic status, with three categories (low, medium and high).Continuous variables are numeric variables that have an infinite number of values between any two values.

Quantitative data is countable or measurable, relating to numbers;Data consist of individuals and variables that give us information about those individuals.In other words, you assign categories to your qualitative data, and then you can order (thus ordinal) them in a logical way.Discrete data refers to certain types of information that cannot be divided into parts.Quantitative analysis cannot be performed on categorical data which means that numerical or arithmetic operations cannot be performed.

Categorical variables contain a finite number of categories or distinct groups.Categorical data always belong to the nominal type.The opposite type of categorical data is ordinal;Quantitative data lends itself to statistical analysis;Quantitative or numerical data are numbers, and that way they 'impose' an order.

Categorical data—the labels that tell us what the numbers measure.Qualitative data is grouped and categorized according to themes.Finishing places in a race), classifications (e.g.Categorical data represent characteristics such as a person's gender, marital status, hometown, or the types of movies they like.Data types are an important aspect of statistical analysis, which needs to be understood to correctly apply statistical methods to your data.

Datasheets are obtained in the form of numerical values.