RESEARCH METHODOLOGY

Detailed explanation-1: -Categorical variables are also known as discrete or qualitative variables. Categorical variables can be further categorized as either nominal, ordinal or dichotomous.

Detailed explanation-2: -A nominal variable with two mutually exclusive categories is sometimes called a dichotomous variable. An ordinal-scale variable has values that can be ranked but are not necessarily evenly spaced, such as stage of cancer (see Table 2.3).

Detailed explanation-3: -The main differences between Nominal Data and Ordinal Data are: While Nominal Data is classified without any intrinsic ordering or rank, Ordinal Data has some predetermined or natural order. Nominal data is qualitative or categorical data, while Ordinal data is considered “in-between” qualitative and quantitative data.

Detailed explanation-4: -Dichotomous variables can either be true dichotomous variables like dead or alive, or they can be continuous, nominal or ordinal variables divided into two categories.

Detailed explanation-5: -Dichotomous variables are categorical variables with two levels. These could include yes/no, high/low, or male/female. To remember this, think di = two. Ordinal variables have two are more categories that can be ordered or ranked.