Variables and Classification

Variables and Classification
The two variables used in the health field are gender and age. Gender is classified as a qualitative variable, whereas age is a quantitative variable. Age is classified as a quantitative variable since it takes numerical values, which represents some measurement. Age takes on multiple numerical variables hence makes sense when in numerical form, thus quantitative. Gender as a variable is classified as a qualitative variable since its data fit into male or female categories that can’t be expressed in any natural order (Holmes, Illowsky, & Dean, 2018).
Levels of measurement
Age as a quantitative variable is continuous and classified in the level of the ratio. The classification of age in the ratio level is because of its absolute zero value at the start, and the difference between age values is significant. For example, a person who is 30 years old has lived (since birth) twice as a person who is 15 years old. Gender is classified as a qualitative variable that falls into a nominal level. Gender has two values: male and female and have no evaluative distinction, which means none of the matters is more significant than the other (“Statistics for health care research,” n.d.).
Sampling Method
The sampling method used to gather the age and gender data in healthcare settings is convenience sampling. Convenience sampling is a non-probability selection that involves a sample been drawn from a population that is close-hand. In our case of health, the data can be captured from any of the patients who visit the health center at the convenience of the researcher (“Statistics for health care research,” n.d.).
Your responses can explain additional analyses that could be done with the variables they selected. Consider confounding variables, discrete or continuous data, the effects of outliers, etc.

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