Two types of variables in statistics

In statistics, there are two main types of variables: Quantitative Variables: These are variables that represent measurable quantities and can be expressed numerically. They are further divided into two types: Discrete Variables: These are countable in a finite amount of time and include a countable number of values. Examples include the number of students in a classroom or the number of cars in a parking lot. Continuous Variables: These can take on any value within a given range and are not countable but measurable. Examples include height, weight, and temperature. Categorical Variables: These are variables that represent characteristics or attributes and can be divided into distinct groups or categories. They are further divided into two types: Nominal Variables: These have two or more categories without any intrinsic order among them. Examples include blood types, gender, and marital status. Ordinal Variables: These have two or more categories with a clear ordering or ranking, but the intervals between the ranks are not necessarily equal. Examples include socioeconomic status (low, middle, high), education level (high school, bachelor's, master's, PhD), and Likert scale responses in surveys (strongly disagree, disagree, neutral, agree, strongly agree). Understanding the type of variable is crucial for determining the appropriate statistical tests and analyses to perform on the data. Two types of Variables A) Qualitative, Nominal B) Quantitative, Ordinal C) Nominal, Quantitative D) Ordinal, Nominal E) Qualitative, Quantitative * Qualitative variables are categorical in nature and represent qualities or characteristics, while quantitative variables are numerical and represent quantities or measurements. two subtypes of qualitative variables, which are nominal (categories with no inherent order) and ordinal (categories with a specific order or ranking).