1 Applied biostatistics Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga, España

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Transcripción de la presentación:

1 Applied biostatistics Francisco Javier Barón López Dpto. Medicina Preventiva Universidad de Málaga, España

2 Data, variables and file

3 Categorical variables: Frequency

4

5 Numeric variables

6 ¿mean and standard deviation are enough?

7 Interpreting mean and standard deviation Centered at the mean, +/- 1 std.dev, there are close to 68% of observations. In a +/- 2 std. Dev. Radius there are close to 95%.

8 If the distributions are close to normal, the interpretation is similar.

9 Tukey diagrams If 2 numbers are not enough… let’s try 5!  Quartiles, minimum, maximum The central box contains 50% of central data.

10 ¿mean or median? Altura mediana

11 When there is strong skewness(asymmetry), probably is better to use the median Depending on the skewness statistics we have negative or positive skewness.  When data is symmetric  asimmetry=0.

12 ¿Flat or peaked: Kurtosis? Kurtosis

13 El IMC, como medida de la relación entre peso y talla, muestra una población con media ajustada a la sobrecarga ponderal (IMC= ) con una clara desproporción hacia la obesidad Poca información… ¿Falta algo?

14 Descritive statistics in just one table

15 When there is something missing in the table, it can be described in the text La media de edad a la Menopausia fue de años para el conjunto de mujeres menopaúsicas. El rango de edades fue de 41 años, con mínimo y máximo en 24 y 65 años, respectivamente. El histograma presentó un elevado índice de curtosis con desproporción hacia los valores inferiores consecuencia, de los efectos de intervenciones quirúrgicas sobre el aparato reproductor femenino. Sólo menopáusicas. No están en la tabla resumen

16

17 Studying two variables at same time Numerical - Numerical Numerical - Categorical Categorical – Categorical

18 Numerical- Numerical Individuals with higher punctuation in one test, have a tendency to have higher punctuation in the other. The relationship is not perfect, so there are more factors involved when trying to use one variable to explain the other.

19 Pearson’s linear correlation coefficient, ‘r’

20 Numerical - Categorical Generally lower values in men than women Greater dispersion in women

21 Categorical - Categorical