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CelebratedCyclops

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Faculty of Nursing

Dr. Nessren Farouk

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variables data analysis statistics public health

Summary

This document is a presentation about different types of variables. The presentation covers qualitative and quantitative variables, nominal and ordinal categories and continuous and discrete variables, using examples appropriate to community medicine.

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Types of variables Dr. Nessren Farouk Lecturer of public health and community medicine A variable It is a value of characteristics that changes from one subject to another, from thing to thing Variables Constants are observations that have defined and same value regardless...

Types of variables Dr. Nessren Farouk Lecturer of public health and community medicine A variable It is a value of characteristics that changes from one subject to another, from thing to thing Variables Constants are observations that have defined and same value regardless of observation unit or setting Light speed, gravitational acceleration,…. Variables are observations that have different values according to the observation unit or setting Age and Gender, Blood Pressure, Weight, Height, Fasting Blood Glucose Qualitative Variables Qualitative or Categorical: in response to the question you choose one category from a list of many mutually exclusive categories: Blood group: A or B or AB or O (only one!) Educational level: illiterate, primary, secondary or university graduate Nationality: Egyptian, English, French. Residence: Governorate Nominal vs. Ordinal Qualitative or Categorical variables can be divided into: Nominal: the categories of the variable have no natural order: Blood groups and nationality Ordinal: the categories of the variable have a natural order: School attendance: none, primary, high, university Social class: low, middle, high Binary variable that has only two categories: Sex: male/female , Disease: affected/free Continuous Quantitative Variables The scale you are using has either Equal intervals: the distances between successive measures are equal but not proportionate Temperature: the difference between 100° and 50° = the difference between 0° and 50° but a temperature of 100° does not mean a double amount of heat compared to 50° There is no true zero, the zero is arbitrary so there is subzero temperatures Equal intervals and equal proportion: the distances between successive measures are equal and proportionate Weight: a 120 Kg man is double the weight of a 60 Kg woman There is true zero or absence of amount Quantitative Variables Discrete vs. Continuous Quantitative variables: the answer to the question is number Number of children in the family, Number of beds in the hospital. The answer is a whole number that is enumerated. Discrete quantitative variables (count). Height, Weight, Blood Pressure, serum cholesterol. The answer is a number with a fraction that is obtained using a scale for measurement. Continuous quantitative variable (measure). Variables = Observations with non-constant values Qualitative or Categories Quantitative Discrete: Number of children Binary: Number of days in Male-Female ICU Smoker-nonsmoker Nominal: Continuous with a scale Blood group of measurement Residence Ordinal: Interval (arbitrary Cancer stage zero): Injury level temperature Ratio (true zero): Height-weight

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