Old men with BP 210/110mm Hg are classified as sever hypertension. This type of data is -
Ans. is 'a' i.e., Categorical o This question is tricky one -# Blood pressure itself is a continuous quantitative data.# But, classification into sever hypertension (wether severe hypertension is present or not) is qualitative (categorical) data.)Statistical datao There are basically two types of variables and they yeild two types of data.i) Categorial (qualitative) variable - yields non numerical (qualitative) data.ii) Numerical (quantitative) variable - Yields numerical (quantitative) data.i) Categorial (qualitative)o Categorial variables yield data in categories i.e., data may be divided into groups,o There is no numerical value - Variable can not be measured directly.o For example response to such question as "what is your sex" or "Do you own a Car" - The answer will be either a category (male or female) or yes/No - No numerical valueso Examples of categorial variables - Race, Sex, Blood group, Pesence of diabetes, obesity, type of anemia.o Qualitative data are measured on nominal and ordinal scales.ii) Numerical (quantitative)o Numerical variables yield data in numerical form - Variable can be measured directlyo For example response to such question "How tall are you" answer may be 4 feet, 5 feet, 5.5 feet.., numerical value.o Quantitative data can be further divided into : -a) Discrete variable# Discrete variable is one that cannot take on all values within the limits of the variable.# For example, response to a five-point rating scale can only take on the values 1, 2, 3, 4 and 5.o The variable cannot have value 1.7.# So, discrete variable has few possible numericle values and no in-between values.# Discrete variable has no unit.# Far example - Number of children in a family, no offamily member; no of patients in a hospital.b) Continuous variable# Variables that can take on any numerical value are called continuous variable.# For example height of a person can be 5 feets, 5.2 feets, 5.5 feets, 6 feets.# So, continuous variable has a unit e.g., Kg, feets.# Examples - Weight, height, mid-arm circumference, blood sugar level, body mass index, serum cholesterol level, hemoglobin level, Bone density measurements, pulse rate, Body temperature.o Quantitative (numerical) data are measured on interval and ratio scales.Following important points require specific mention here : -o Though qualitative (categorial) data do not have numerical value, some times numerical value is used to classify the limit of qualitative data. For example : -1) All low birth weight children will have birth weight less than 2500 gm. So,a) Birth weight (which may be 2200 gm, 2500 gm, 2600 gm) is a continuous variable.b) Low birth weight (< 2500 gm) is a qualitative data because either a newborn have low birth weight or not.2) Blood cholesterol level (which may be 70, 80, 90, 200 mg/dl) is a quantitative variable but when it comes high or low blood cholesterol level, it becomes qualitative variable because a preson may either have low or high cholesterol level.3) Similarly blood sugar level is quantitative variable, while high or low blood sugar (presence or absence of diabetes) is a qualitative variable.4) Blood hemoglobin is a quantitative variable, while high or low hemoglobin (Presence or absence of anemia) is a qualitative variable.Note:o Pulse rate (PR) is considered as a continuous variable.o Immediately question comes to mind that how can pulse rate be a continues variable when pulse rate can only be 70/71... beats per minute but not in between value (70.1, 70.5 ...). However, this is only true when we count pulse for only 1 minute.o In other scenario, if the pulse rate is counted for 3 minutes and it comes 216, then the pulse rate will be 72.3 beats per minute - Therefore, pulse rate is considered as a continuous variable.
Categorical
Numerical
Quantitative
Continuous
Data Variables