Transcript 32911

Course on Biostatistics
Part 1
What is statistics?
Dr. Nicolas Padilla Raygoza
Department of Nursing and Obstetrics
Division of Health Sciences and Engineering
Campus Celaya Salvatierra
University of Guanajuato, Mexico
Biosketch
 Medical Doctor by University Autonomous of
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Guadalajara.
Pediatrician by the Mexican Council of Certification
on Pediatrics.
Postgraduate Diploma on Epidemiology, London
School of Hygiene and Tropical Medicine, University
of London.
Master Sciences with aim in Epidemiology, Atlantic
International University.
Doctorate Sciences with aim in Epidemiology,
Atlantic International University.
Professor Titular A, Full Time, University of
Guanajuato.
[email protected] [email protected]
Competencies
 The reader will describe what is statistics.
 He (She) will describe what is descriptive and
inferential statistics.
 He (She) will know what are the applications
of statistics.
Introduction
 Statistics
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The number that we obtain by count o
measure things.
Procedures to analyze the data.
 Descriptive statistics
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It is the methods to describe an data set.
We use it to organize, to summary and to
present the values of data.
Introduction
 Statistics
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Last, “the science and art of collecting,
summarizing, and analyzing data that are
subject to random variation”.
 It is classified into:
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Descriptive
Inferential
Descriptive statistics - Examples
 In a cohort study on risk factors to coronary
heart disease, it was measure the levels of
cholesterol in blood; we can show the mean
and standard deviation.
Level cholesterol in blood X = 268 S ± 49
Descriptive statistics-Examples
 In a cross-sectional
study in a group of
children, it was
determine the
gender of the
subjects and it was
determine
frequency and
percentage of
males and
females; it can be
shown in graphical
form.
Variable
Sex
Male
n
%
64
36
64
36
100
100
Female
Total
Distribution by sex, n=100
Female
36.0%
Male
64.0%
Inferential statistics
 It use the probability theory to obtain
conclusions of a population, from data
obtained in a sample.
 It is very hard to study all population, because
of this, we study samples.
 Methods for estimations and hypothesis tests
are important to obtain inferences.
Inferential statistics - Examples
 In a National survey on the danger of
smoking, we cannot interview all population,
only we can interview a sample of it.
 To measure prevalence of amebiasis in a
population, we study a random sample. With
the prevalence of the sample, we can obtain
the estimate of prevalence of amebiasis in
the population.
Applications of statistics
 To obtain a sample.
 To summary data.
 Make inferences of a population, based in the
result of the sample.
 To obtain a simple model for a data set.
Bibliografia
 1.- Last JM. A dictionary of epidemiology.
a
New York, 4 ed. Oxford University Press,
2001:173.
 2.- Kirkwood BR. Essentials of medical
ststistics. Oxford, Blackwell Science, 1988: 14.
 3.- Altman DG. Practical statistics for medical
research. Boca Ratón, Chapman & Hall/
CRC; 1991: 1-9.