Data and Variable Types PDF

Data and variable types Learning Objectives ○Understand the concept of variable ○Distinguish the types of variables ○Select the variables relevant to study ○Perform appropriate data transformation Definition Of Variable ○“Any characteristic that varies from one member of a population to anoth...

Data and variable types Learning Objectives ○Understand the concept of variable ○Distinguish the types of variables ○Select the variables relevant to study ○Perform appropriate data transformation Definition Of Variable ○“Any characteristic that varies from one member of a population to another. A simple example is height in centimeters, which varies from person to person  Types of Variables Quantitative Qualitative (numerical ) (categorical )  I- Quantitative Variables ○Data in numerical quantities that can assume all possible values ○Data on which mathematical operations are possible ○Example: age, weight, temperature, haemoglobin level, RBCs count Discrete ○ Reflects a number obtained by counting—no decimal. ○ Examples: number of employees of a company number of incorrect answers on a test number of participants in a program… Continuous Reflects a measurement; the number of decimal places depends on the precision of the measuring device. ○ Examples: Age Income ○ Arithmetic operations such as differences and averages make sense. II- Qualitative Variables Qualitative variables are those having exact values that can fall into number of separate categories with no possible intermediate levels Nominal Ordinal 1- Nominal Variable Unordered qualitative categories Dichotomous Multichotomous (2 categories) (> 2 categories) Gender marital status 2- Ordinal Variable Ordered qualitative categories Score birth order Categorical social class  Data Quantitative Qualitative (numeric) (categorical) Continuous Discrete Ordinal Nominal (height, weight, (N. student, (degree of (bloodgroup, age) pulse) hypertension Gender) Data Collection Tool Age in years: Gender: 1) male, 2) female Social class: 1) low, 2) middle, 3) high Height in cm:. Data Reduction Example ○Data: Age from 47 individuals ○Arrange in ascending order: 20, 21, 22, 23, 23, 24, 25, 29,29, 30, 30, 34, 34, 34, 34, 34, 34, 35, 35, 36, 37, 39, 39, 40, 43, 43, 43, 46, 46, 47, 47, 48, 48, 48, 50, 52, 56, 56, 58, 59, 59, 60, 62, 64, 64, 67, 69 Data Reduction Continuous: 20, 21, 22…….69 Interval: 20-29, 30-39, 40-49, 50-59, 60-69 Ordinal: Twenties, Thirties, Forties, Fifties, Sixties Nominal: Young or Old Decide whether the variables shown contain data that is nominal, ordinal, discrete or continuous ○ Smoking status (smoker, non-smoker) ○ Satisfaction level ○ Blood glucose level ○ Type of exercise (low, moderate, vigorous) ○ Number of cars in car park ○ Number of children in family ○ Marital status ○ Weight ○ Time taken to complete a task  Conclusion The variable is the basic unit required to perform a research. The researcher has to select the list of variables relevant to the study objectives. The type of variable should be set in order to allow for proper data collection, transformation and presentation.