1. Gender (male/female) is not a quantitative variable.
Quantitative information is often called data, but can also be things other than numbers. Qualitative Information – Involves a descriptive judgment using concept words instead of numbers. Gender, country name, animal species, and emotional state are examples of qualitative information.
The data corresponding to gender of the subjects is a qualitative data.
A qualitative nominal variable is a qualitative variable where no ordering is possible or implied in the levels. For example, the variable gender is nominal because there is no order in the levels female/male. Eye color is another example of a nominal variable because there is no order among blue, brown or green eyes.
Sex is usually categorized as female or male but there is variation in the biological attributes that comprise sex and how those attributes are expressed. Gender refers to the socially constructed roles, behaviours, expressions and identities of girls, women, boys, men, and gender diverse people.
Nominal scales Gender is an example of a nominal measurement in which a number (e.g., 1) is used to label one gender, such as males, and a different number (e.g., 2) is used for the other gender, females. Numbers do not mean that one gender is better or worse than the other, they simply are used to classify persons.
For example, gender is a categorical data because it can be categorized into male and female according to some unique qualities possessed by each gender.
Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form. For example, it could be notes taken during a focus group on the quality of the food at Cafe Mac, or responses from an open-ended questionnaire.
A categorical or discrete variable is one that has two or more categories (values). For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories.
(a) Gender is a qualitative variable because it allows a researcher to categorize the individual as male or female.
Gender is used to describe the characteristics of women and men that are socially constructed, while sex refers to those that are biologically determined. People are born female or male, but learn to be girls and boys who grow into women and men.
Gender refers to the characteristics of women, men, girls and boys that are socially constructed. This includes norms, behaviours and roles associated with being a woman, man, girl or boy, as well as relationships with each other. As a social construct, gender varies from society to society and can change over time.
These categories have corresponding numbers allotted for analysis of collected data. For example, a person's gender, ethnicity, hair color etc. Here, the data collected will be on an ordinal scale as there is a rank associated with each of the answer options, i.e. 2 is lower than 4 and 4 is lower than 5.
What is Categorical Data? Categorical data is a type of data that can be stored into groups or categories with the aid of names or labels. For example, gender is a categorical data because it can be categorized into male and female according to some unique qualities possessed by each gender.
Here are some example of quantitative data:A jug of milk holds one gallon.The painting is 14 inches wide and 12 inches long.The new baby weighs six pounds and five ounces.A bag of broccoli crowns weighs four pounds.A coffee mug holds 10 ounces.John is six feet tall.A tablet weighs 1.5 pounds.
Examples of Qualitative DataDiary accounts. Diary accounts are collected as part of diary studies. Documents. Case studies. Photographs. Audio recordings. Video recordings. Transcriptions. Descriptions.
Quantitative data are measures of values or counts and are expressed as numbers. Qualitative data are measures of 'types' and may be represented by a name, symbol, or a number code. Qualitative data are data about categorical variables (e.g. what type).
Dichotomous variables are nominal variables which have only two categories or levels. For example, if we were looking at gender, we would most probably categorize somebody as either "male" or "female". This is an example of a dichotomous variable (and also a nominal variable).
What are the four genders? The four genders are masculine, feminine, neuter and common. There are four different types of genders that apply to living and nonliving objects.
Gender is a concept that can be broken down into three categories: gender identity, gender expression and physical sex. Gender is not fixed and can change over time. Gender identity is how a person sees themselves. It is their internal sense and personal experience of gender.
A good example of a nominal variable is sex (or gender). Information in a data set on sex is usually coded as 0 or 1, 1 indicating male and 0 indicating female (or the other way around--0 for male, 1 for female).
The hair colors of players on a football team, the color of cars in a parking lot, the letter grades of students in a classroom, the types of coins in a jar, and the shape of candies in a variety pack are all examples of qualitative data so long as a particular number is not assigned to any of these descriptions.
The hair colors of players on a football team, the color of cars in a parking lot, the letter grades of students in a classroom, the types of coins in a jar, and the shape of candies in a variety pack are all examples of qualitative data so long as a particular number is not assigned to any of these descriptions.
Examples of qualitative characteristics are gender, race, genotype and vital status. Qualitative variables are also called categorical variables.
Discrete data: when the variable is restricted to specific defined values. For example, "male" or "female" are categorical discrete data values. Mortality (eg. 20 patients dead at 6 months) is an example of numerical discrete data values.
categorical variableA nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories.
To summarize, gender is typically considered a dichotomous variable, it is certainly a categorical variable.
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