# 33351 - Biostatistics course Part 3 Data summary and...

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Biostatistics course Part 3 Data, summary and presentation Dr. en C. Nicolás Padilla Raygoza Facultad de Enfermería y Obstetricia de Celaya Universidad de Guanajuato México

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Biosketch Medical Doctor by University Autonomous of Guadalajara. Pediatrician by the Mexican Council of Certification on Pediatrics. Postgraduate Diploma on Epidemiology, London School of Hygine and Tropical Medicine, University of London. Master Sciences with aim in Epidemiology, Atlantic International University. Doctorate Sciences with aim in Epidemiology, Atlantic International University. Associated Professor B, School of Nursing and Obstetrics of Celaya, university of Guanajuato.
Competencies The reader will describe type of variables. He (she) will analyze how summary shows the different variables He (she) will calculate central trend measures and find them in graphics. He (she) will calculate dispersion measures and find them in graphics.

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Definitions Data are collected on the specific characteristics of each subject, and groups are formed to be compared. These characteristics are called variables, because they can change from each subject. Variable is obtained because it is: A result of interest - dependent variable Or it explain the dependent variable - risk factor - independent variable.
Type of data Classification for its measurement scale: Qualititative Binary - dichotomous Ordinal Nominal Quantitative Discrete Continuous

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Type of data - Examples Qualitative Dichotomous - binary Gender: male or female. Employment status: employment or without employment. Ordinal Socioeconomic level: high, medium, low. Nominal Residency place: center, North, South, East, West. Civil status: single, married, widowed, divorced, free union. Quantitative Discrete Number of offspring: 1,2,3,4. Continuous Glucose in blood level: 110 mg/dl, 145 mg/dl.
Data summary Generally, we want to show the data in a summary form. Number of times that an event occur, is of our interest, it show us the variable distribution. We can generate a frequency list quantitative or qualitative.

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Summary of categorical data We can obtain frequencies of categorical data and summary them in a table or graphic. Example: we have 21 agents of parasitic diseases isolated from children. Giardia lamblia Entamoeba histolytica Ascaris lumbricoides Enterobius vermicularis Ascaris lumbricoides Enterobius vermicularis Giardia lamblia Giardia lamblia Entamoeba histolytica Ascaris lumbricoides Enterobius vermicularis Ascaris lumbricoides Enterobius vermicularis Giardia lamblia Giardia lamblia Entamoeba histolytica Ascaris lumbricoides Enterobius vermicularis Ascaris lumbricoides Enterobius vermicularis Giardia lamblia
Summary of categorical data List of parasites detected show us an idea of the frequency of each parasite, but that is not clear.

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