Types of Data Collection
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Module 2 discusses the types of data encountered in public health, emphasizing the importance of understanding different data types for proper interpretation. It categorizes data into numerical (discrete and continuous) and categorical variables (nominal and ordinal), with explanations and examples for each type. Additionally, it includes a brief overview of datasets and data tables, providing definitions for various variables used in health assessments.
Types of Data Collection
- 1. Module 2: Types of Data This module describes the types of data typically encountered in public health applications. Recognizing a nd understanding the different data types is an important component of proper data use and interpretation.
- 2. Data and Variables Data are often discussed in terms of variables, where a variable is: 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.
- 3. Types of Variables There are two basic types of variables: numerical and categorical variables. Numerical Variables: variables to which a number is assigned as a quantitative value. Categorical Variables: variables defined by the classes or categories into which an individual member falls. “ “
- 4. Types of Numerical variables • Discrete: Reflects a number obtained by counting—no decimal. • Continuous: Reflects a measurement; the number of decimal places depends on the precision of the measuring device. • Ratio scale: Order and distance implied. Differences can compared; has a true zero. Ratios can be compared. Examples: Height, weight, blood pressure • Interval scale: Order and distance implied. Differences can be compared; no true zero. Ratios cannot be compared. Example: Temperature in Celsius.
- 5. Ratio Scale 11 02 03 04 Add Contents Title You can simply impress your audience and add a unique zing. Add Contents Title You can simply impress your audience and add a unique zing. Add Contents Title You can simply impress your audience and add a unique zing. Add Contents Title You can simply impress your audience and add a unique zing.
- 6. Categorical Variables Defined by the classes or categories into which an individual member falls. • Nominal Scale: Name only--Gender, hair color, ethnicity • Ordinal Scale: Nominal categories with an implied order--Low, medium, high.
- 7. NOMINAL SCALE b. Appearance of plasma: b. 1. Clear……………………… 1. 2. Turbid…………………… 2. 9. Not done………………… 9.
- 8. ORDINAL SCALE 81.Urine protein (dipstick reading): 81. 1. Negative………………… 1. 2. Trace……………………. 2. 3. 30 mg% or +…………… 3. 4. 100 mg% or ++………… 4. 5. 300 mg% or +++……… 5. 6. 1000 mg% or ++++…… 6. If urine protein is 3+ or above, be sure su bject gets a 24 hour urine collection contai ner and instruction
- 9. Likert Scale Compared to others, what is yo ur satisfaction rating of the Nati onal Practitioner Data Bank? Question: 1 2 3 4 5 VerySatisfied SomewhatSatisfied Neutral SomewhatDissatisfied VeryDissatisfied
- 10. Datasets and Data Tables Dataset: Data for a group of variables for a collection of persons. Data Table: A dataset organized into a table, with one column for each variable and one row for each person.
- 11. Typical Data Table OBS AGE BMI FFNUM TEMP( 0F) GENDER EXERCISE LEVEL QUESTION 1 26 23.2 0 61.0 0 1 1 2 30 30.2 9 65.5 1 3 2 3 32 28.9 17 59.6 1 3 4 4 37 22.4 1 68.4 1 2 3 5 33 25.5 7 64.5 0 3 5 6 29 22.3 1 70.2 0 2 2 7 32 23.0 0 67.3 0 1 1 8 33 26.3 1 72.8 0 3 1 9 32 22.2 3 71.5 0 1 4 10 33 29.1 5 63.2 1 1 4 11 26 20.8 2 69.1 0 1 3 12 34 20.9 4 73.6 0 2 3 13 31 36.3 1 66.3 0 2 5 14 31 36.4 0 66.9 1 1 5 15 27 28.6 2 70.2 1 2 2 16 36 27.5 2 68.5 1 3 3 17 35 25.6 143 67.8 1 3 4 18 31 21.2 11 70.7 1 1 2 19 36 22.7 8 69.8 0 2 1 20 33 28.1 3 67.8 0 2 1
- 12. Definitions for Variables • AGE: Age in years • BMI: Body mass index, weight/height2 in kg/m2 • FFNUM: The average number of times eating “fast food” in a week • TEMP: High temperature for the day • GENDER: 1- Female 0- Male • EXERCISE LEVEL: 1- Low 2- Medium 3- High • QUESTION: Compared to others, what is your satisfaction rating of the National Practitioner Data Bank? 1- Very Satisfied 2- Somewhat Satisfied 3- Neutral 4- Somewhat dissatisfied 5- Dissatisfied
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