Applied biostatistics
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1 Applied biostatistics Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga – España [email protected]
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Applied biostatistics. Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga – España [email protected]. Statistical inference. Talking about the population, knowing just samples. Usually high probability of being right (95%) or low of being wrong (5%) Usually: - PowerPoint PPT Presentation
Transcript of Applied biostatistics
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Applied biostatistics
Francisco Javier Barón LópezDpto. Medicina PreventivaUniversidad de Málaga – Españ[email protected]
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Statistical inference
Talking about the population, knowing just samples.
Usually high probability of being right (95%) or low of being wrong (5%)
Usually: Confidence interval (C.I. 95%) Statistical test (p<0,05)
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For both ways we need: Standard Error
Easy to interpret (believe me):We hope the estimate (sample) being near the
real value (population). How close? There is a 95% probability of the estimate being not
far away than 2 standard errors of the population parameter.
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Example
Simulation: Let’s get samples from different size of the population and see what happens when we try to estimate the population mean, using the sample mean.
Starting with sample size n=4…
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Aplic. de la normal: Estimación en muestras
The distribution of sample means are almost “normal”
It is not as dispersed as the population. It’s S.D it is called standard error (s.e.)
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Aplic. de la normal: Estimación en muestras
If n grows:
The sample mean distribution is more gaussian.
Standard error decreases.
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Aplic. de la normal: Estimación en muestras
Puedo ‘garantizar’ medias muestrales tan cercanas como quiera a la verdadera media, sin más que tomar ‘n bastante grande’
Se utiliza esta propiedad para dimensionar el tamaño de una muestra antes de empezar una investigación.
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Sample size Mean Std. Error
answer
10 women 77 6 No evidence against
100 women 71 1.6 No
1000 women 73 0.5 No
•Mean value of BUA in young women is 85. ¿women extracted from sample are similar?
•Use 95% confidence
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Simulation
Let’s take samples of size 4.
70 75
Do smokers weight more than non smokers?
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Let’s take samples of size n=3070 75
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Let’s take amples of size 4.
Two types of error are possible
70 75
No differences Accept differences
type II error
Type I error
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, p, statistical significance
statistical significance = p <
Estadísticos de contrastea
259753,500
462319,500
-2,317
,021
U de Mann-Whitney
W de Wilcoxon
Z
Sig. asintót. (bilateral)
Edad delencuestado
Variable de agrupación: Sexo del encuestadoa.
