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Describing. Type of data FETP India. Competency to be gained from this lecture. Identify the different types of data to use appropriate methods to describe their distribution. Key issues. Qualitative data Quantitative data Distribution. Data: A definition. Set of related numbers
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Describing Type of dataFETP India
Competency to be gained from this lecture Identify the different types of data to use appropriate methods to describe their distribution
Key issues • Qualitative data • Quantitative data • Distribution
Data: A definition • Set of related numbers • Raw material for statistics • Example: • Temperature of a patient over time • Date of onset of patients Data
Epidemiological process • We want to describe a population • We collect data • We analyze data into information • “Data reduction” • We interpret the information • We use the information for decision making Data
Types of data • Qualitative data • No magnitude / size • Classified by counting the units that have the same attribute • Types: • Binary • Nominal • Ordinal • Quantitative data Qualitative
Qualitative, binary data • The variable can only take two values • 1, 0 • Yes, No • Example: • Sex • Male, female • Female sex • Yes, No Qualitative
REC SEX --- ---- 1 M 2 M 3 M 4 F 5 M 6 F 7 F 8 M 9 M 10 M 11 F 12 M 13 M 14 M 15 F 16 F 17 F 18 M 19 M 20 M 21 F 22 M 23 M 24 F 25 M 26 M 27 M 28 F 29 M 30 M Frequency distribution for a qualitative binary variable Qualitative
Using a pie chart to display qualitative binary variable Qualitative Distribution of cases by sex
Qualitative, nominal data • The variable can take more than two values • Any value • The information fits into one of the categories • The categories cannot be ranked • Example: • Nationality • Language spoken • Blood group Qualitative
REC NATION --- ------- Frequency distribution for a qualitative nominal variable 1 JORDAN 2 YEMEN 3 IRAN 4 JORDAN 5 YEMEN 6 JORDAN 7 YEMEN 8 TCHAD 9 SUDAN 10 IRAN 11 YEMEN 12 IRAN 13 JORDAN 14 SUDAN 15 IRAN 16 SUDAN 17 JORDAN 18 SUDAN 19 IRAN 20 YEMEN 21 SUDAN 22 YEMEN 23 SUDAN 24 IRAN 25 YEMEN 26 YEMEN 27 YEMEN 28 SUDAN 29 YEMEN 30 SUDAN
Using a horizontal bar chart to display qualitative nominal variable Qualitative Distribution of cases by nationality
Qualitative, ordinal data • The variable can only take a number of value than can be ranked through some gradient • Example: • Severity • Mild, moderate, severe • Vaccination status • Unvaccinated, partially vaccinated, fully vaccinated Qualitative
REC Status --- ------- 1 1 2 1 3 2 4 2 5 1 6 2 7 1 8 2 9 3 10 2 11 1 12 3 13 1 14 3 15 1 16 3 17 1 18 1 19 3 20 1 21 1 22 2 23 1 24 2 25 2 26 1 27 2 28 3 29 2 30 2 Frequency distribution for a qualitative ordinal variable Clinical status: 1: Mild; 2 : Moderate; 3 : Severe
Using a vertical bar chart to display qualitative ordinal variable Qualitative Distribution of cases by severity
Key issues • Qualitative data • Quantitative data • We are not simply counting • We are also measuring • Discrete • Continuous Quantitative
Quantitative, discrete data • Values are distinct and separated • Normally, values have no decimals • Example: • Number of sexual partners • Parity • Number of persons who died from measles Quantitative
REC CHILDREN --- ------- 1 1 2 2 3 5 4 6 5 3 6 4 7 1 8 1 9 2 10 3 11 1 12 2 13 7 14 3 15 4 16 2 17 1 18 1 19 1 20 1 21 2 22 3 23 1 24 4 25 2 26 1 27 6 28 4 29 3 30 1 Frequency distribution for a quantitative, discrete data
Using a histogram to display a discrete quantitative variable Quantitative Distribution of households by number of children
Quantitative, continuous data • Continuous variable • Can assume continuous uninterrupted range of values • Values may have decimals • Example: • Weight • Height • Hb level • What about temperature? Quantitative
REC WEIGHT --- ------ 1 10.5 2 23.7 3 21.8 4 33.1 5 38.0 6 34.5 7 38.5 8 38.4 9 30.1 10 34.7 11 37.9 12 38.0 13 39.2 14 30.1 15 43.2 16 45.7 17 40.4 18 56.4 19 55.1 20 55.4 21 66.7 22 82.9 23 109.7 24 120.2 25 10.4 26 10.8 27 25.5 28 20.2 29 27.3 30 38.7 Frequency distribution for a continuous quantitative variable: The tally mark
REC WEIGHT --- ------ 1 10.5 2 23.7 3 21.8 4 33.1 5 38.0 6 34.5 7 38.5 8 38.4 9 30.1 10 34.7 11 37.9 12 38.0 13 39.2 14 30.1 15 43.2 16 45.7 17 40.4 18 56.4 19 55.1 20 55.4 21 66.7 22 82.9 23 109.7 24 120.2 25 10.4 26 10.8 27 25.5 28 20.2 29 27.3 30 38.7 Frequency distribution for a continuous quantitative variable, after aggregation
Using a histogram to display a frequency distribution for a continuous quantitative variable, after aggregation Quantitative Distribution of cases by weight
Series of 100 values of a quantiative variable 87.0 84.0 51.1 64.9 71.5 88.8 62.7 14.2 87.0 44.7 48.9 27.8 88.3 39.9 11.1 64.0 31.4 32.6 73.4 34.8 89.7 56.1 37.9 67.5 38.3 32.6 33.1 52.0 62.9 39.5 44.6 56.6 82.1 70.3 83.6 34.3 78.7 52.1 63.1 82.4 50.2 43.0 16.6 78.2 72.7 11.1 49.7 32.6 49.4 79.1 18.9 64.7 37.1 74.2 88.9 59.7 82.5 69.3 81.5 72.3 61.9 34.9 48.1 18.7 54.9 46.4 58.9 39.4 66.9 47.9 40.9 74.9 31.1 55.8 57.6 37.6 23.3 44.4 21.8 81.6 21.6 75.7 35.9 33.9 24.6 77.2 30.0 48.1 18.7 67.6 52.3 24.3 48.9 76.3 43.2 Quantitative 17.3 43.9 76.2 45.0 55.7
Tabular and graphic representation of a distribution Values Frequency 0-9 0 10-19 8 20-29 7 30-39 18 40-49 16 50-59 13 60-69 11 70-79 14 80-89 13 90-99 0 Total 100 Distribution
Describing a distribution Position Dispersion
Summary Qualitative Binary Nominal Ordinal Sex Nationality Status M Yemen Mild M Jordan Moderate F Yemen Severe M Jordan Mild F Sudan Moderate F Yemen Mild M Sudan Moderate M Iran Severe F Jordan Severe M Iran Mild F Yemen Moderate F Sudan Moderate M Iran Mild M Yemen Severe M Jordan Severe F Jordan Moderate M Iran Mild F Sudan Mild M Yemen Mild Quantitative Discrete Continuous Children Weight 1 56.4 1 47.8 2 59.9 3 13.1 1 25.7 1 23.0 2 30.0 3 13.7 2 15.4 2 52.5 1 26.6 1 38.2 1 59.0 2 57.9 2 19.6 3 31.7 2 15.1 3 33.9 1 45.6
Data type in computer software Avoid free field variables difficult to analyze
Exercise • Consider the class • Describe the frequency distribution of the following variable: • Sex • State of origin • Involvement in surveillance to date (None, partial, full time) • Completed numbers of years in service • Height in cm
Take home messages • Qualitative data can be binary, nominal or ordinal • Quantitative data can be discrete or continuous • Distribution can be described with a table or a graph