MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Objective 1.2Discrete data is often referred to as categorical data because of the way observations can be collected into categories. Variables producing such data can be of any of the following types: Nominal (e.g., gender, ethnic background, religious or political affiliation)

Detailed explanation-2: -Categorical variables are also known as discrete or qualitative variables. Categorical variables can be further categorized as either nominal, ordinal or dichotomous. Nominal variables are variables that have two or more categories, but which do not have an intrinsic order.

Detailed explanation-3: -Categorical variables, aka discrete variables. These come in only a fixed number of values – like dead/alive, obese/overweight/normal/underweight, Apgar score. Continuous variables. These can have any value between a theoretical minimum and maximum, like birth weight, BMI, temperature, neutrophil count.

Detailed explanation-4: -Categorical variables A categorical variable (also called qualitative variable) refers to a characteristic that can’t be quantifiable. Categorical variables can be either nominal or ordinal.

Detailed explanation-5: -The most important difference between the terms is that “continuous data” describes the type of information collected or entered into study. In contrast, “categorical data” describes a way of sorting and presenting the information in the report.