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Variables

Variables. Sherine Shawky , MD, Dr.PH Assistant Professor Department of Community Medicine & Primary Health Care College of Medicine King Abdulaziz University . Learning Objectives. Understand the concept of variable Distinguish the types of variables Recognize data processing methods.

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Variables

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  1. Variables Sherine Shawky, MD, Dr.PH Assistant Professor Department of Community Medicine & Primary Health Care College of Medicine King Abdulaziz University

  2. Learning Objectives • Understand the concept of variable • Distinguish the types of variables • Recognize data processing methods

  3. Performance Objectives • Select the variables relevant to study • Perform appropriate data transformation • Present data appropriately

  4. Definition Of Variable “A variable is any quantity that varies. Any attribute, phenomenon or event that can have different values”

  5. Information Supplied By Variables Indices of Person Indices of Place Indices of Time

  6. Specification of Variable Clear precise standard definition Method of measurement Scale of measurement

  7. Role Of Variable Correlation Interdependent Interdependent

  8. Role Of Variable Association Independent Dependent Independent Independent Effect modifier Confounding Dependent Dependent

  9. Types of Variables Quantitative (continuous) Qualitative (Discrete)

  10. 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

  11. 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

  12. 1- Nominal Variable Unordered qualitative categories Dichotomous (2 categories) Multichotomous (> 2 categories)

  13. 2- Ordinal Variable Ordered qualitative categories Score birth order Categorical social class Numerical discrete parity

  14. Continuous & Numerical Discrete Variables Continuous Variable -3 -2 -1 0 1 2 3 Numerical Discrete 0 1 2 3

  15. Types of Variables - Quantitative How much? - Dichotomous - Multichotomous - Score - Categorical Who, How, where, when, What,…etc.? - Numerical discrete How many?

  16. Data Collection Tool Age in years: Gender: 1) male, 2) female Social class: 1) low, 2) middle, 3) high Height in cm: .

  17. Data Transformation Data Reduction Creation of composite variable

  18. 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

  19. Data Reduction Example (cont.) • Calculate the range: 69-20= 49 • No. of intervals= 5 • Width of class= 49/5 = 9.8  10 • Class intervals= 20-29, 30-39, 40-49, 50-59, 60-69

  20. 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

  21. Creation Of Composite Variable Single variables Composite variable Quantitative Quantitative Qualitative Qualitative

  22. Data Presentation Tabular Diagrammatic

  23. Data Presentation Variable Table Chart Frequency Pie Nominal - - Percentage Column or Bar - - Frequency Pie Ordinal - - Percentage Column or Bar - - Cumulative Linear - - Ogive frequency - Cumulative - percentage Frequency Histogram Interval - - Percentage Frequency - - Cumulative - polygon Ogive frequency - Cumulative - percentage Mean, SD Scatter Continuous - - Mean, Box plot - - 95 %CI

  24. Frequency Table

  25. Pie Chart

  26. Column Chart All categories Single Category %

  27. Bar Chart All categories Single Category %

  28. Frequency and Cumulative Frequency Table

  29. Linear Chart Ogive (Cumulative Percentage) Percentage Stages of Breast Cancer

  30. Frequency and Cumulative Frequency Table for Variable of Interval

  31. Horizontal axis For Variable of Interval

  32. Histogram % %

  33. Frequency Polygon %

  34. Tabular Presentation of Quantitative Data or Variable Total Mean SD 95 % CI Age 47 42 . 1 . 38 . 2 - 46 . 0 13 5 (years)

  35. Scatter Diagram

  36. Box-whisker plot 80 70 60 AGE in years 50 40 30 20 10 Male Female 20 N = 27 SEX

  37. 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, specify every piece of information and assign its role. The type of variable should be set in order to allow for proper data collection, transformation and presentation.

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