ANOVA de un factor

Caso 1

1. Descargue la base ANOVA1

2. Codebook, compact

3. Desarrolle el modelo ANOVA

a. Statistics

b. Linear models an related

c. ANOVA/MANOVA

d. One-way ANOVA

Response variable: stemcell

Factor variable: partyid

La respuesta o variable dependiente debe ser cuantitativa y la variable independiente o

factor variable es categrica.

4. Multiple-comparison tests, seleccione Bonferroni

Se pueden elegir tre Bonferroni, Scheffe y Sidak. Son tres procedimientos para comparar

cada par de las medias

5. OK

female 46 2 .4782609 0 1 1 if female, 0 if mailpartyid 46 4 2.391304 1 4 party identificationstemcell 46 8 6.26087 1 9 support for stem cell research Variable Obs Unique Mean Min Max Label

. codebook, compact

Se evala el valor de Prob>F, si es mayor a 0.05 no hay relacin, si es menor a 0.05 si hay relacin

Origen de las variaciones. El anlisis de la varianza requiere la estimacin de dos varianzas:

entre grupos (stemcell, apoyo a la investigacin de clulas madre) y la de grupos (identidad

partidista)

Suma de cuadrados: suma de las desviaciones al cuadrado

Grados de libertad:

o Entre grupos es 4, nmero de partidos menos 1

o Dentro de los grupos es 42. (nmero de observaciones-el nmero de partidos)

Promedio de los cuadrado: (varianzas estimadas)= Suma de cuadrados/grados de libertad.

(92.70/3=309, y 104.16/42=2.48)

F: es la distribucin de probabilidad. Es el cociente de dos varianzas. (30.900/2.48=12.46)

Probabilidad. Este es el valor que responde a la pregunta. Queremos saber si hay algn

tipo de relacin entre las carreras y las calificaciones. El anlisis de varianza (ANOVA) asume por

default que no hay relacin. Como regla general:

o Si la probabilidad es mayor que 0.05 significa que se cumple no se rechaza la

hiptesis: No hay relacin.

o Si la probabilidad es menor de 0.05 se rechaza la hiptesis, es decir hay algn tipo de

relacin entre las carreras y las calificaciones.

0.000 1.000 0.015noninvol -3.25 .083333 -2.25 0.684 0.003independ -1 2.33333 0.000republic -3.33333 Col Mean democrat republic independRow Mean- (Bonferroni) Comparison of support for stem cell research by party identification

Bartlett's test for equal variances: chi2(3) = 20.1167 Prob>chi2 = 0.000

Total 196.869565 45 4.37487923 Within groups 104.166667 42 2.48015873Between groups 92.7028986 3 30.9009662 12.46 0.0000 Source SS df MS F Prob > F Analysis of Variance

Total 6.2608696 2.0916212 46 noninvolv 4.75 .88640526 8 independe 7 .78446454 14 republica 4.6666667 2.6053558 12 democrat 8 1.2060454 12 ion Mean Std. Dev. Freq.identificat research party Summary of support for stem cell

. oneway stemcell partyid, bonferroni tabulate

Compara las medias de los grupos, que involucra 6 pruebas

de significancia

Democracia vs Independientes,

Demcratas vs noinvolved,

Republican vs independent,

Republican vs noinvolved

Independient vs noinvol

Si la p

Caso 2

Cuando se tienen encuestas donde las respuestas son categricas, por ejemplo de acuerdo, no lo

s y no estoy de acuerdo. Se debe hacer la siguiente asignacin

De acuerdo=1

No lo se=2

No estoy de acuerdo=3

En este caso se usa las pruebas de rango Kruskal-Wallis para comparar los valores de las medianas

entre los grupos. Si estamos interesados en la identificacin de las diferencias entre los partidos y

el apoyo a la investigacin de las clulas madre. Para ello se seguir el siguiente procedimiento:

1. Statistics

2. Summaries, tables and test

3. Nonparametric tests of hypothese

4. Kruskal-Wallis Rank test

5. Outcome variable: stemcell

6. Variable defining groups: partyid

Se obtienen los siguientes resultados Esta prueba ordena las observaciones del valor ms bajo al

ms alto. Con una escala de rangos de 1 a 9, hay muchos

vnculos, y el programa los ajusta. Si los grupos no fueron

diferentes, la suma de los rangos para cada grupo sera la

misma, asumiendo igual nmero de observaciones. Cuando

se comparan los resultados de la columna Rank Sum se

puede afirmar que los demcratas tienen mayor calificacin

que los republicanos. Dado que cuando se observa que la

probabilidad es menor a 0.05 se puede afirmar que las

diferencias entre los grupos que apoyan la investigacin de

clulas madre son significativas

Puesto que estamos tratando los datos como ordinales tiene sentido hacer uso de las

medianas y no de las medias, para ello desarrolle el siguiente procedimiento:

1. Statistics

2. Summaries, tables and test

3. Tables

4. Table of summary statistics (tabstat)

probability = 0.0001chi-squared with ties = 22.696 with 3 d.f.

probability = 0.0001chi-squared = 22.115 with 3 d.f.

noninvolved 8 94.00 independent 14 391.00 republican 12 174.00 democrat 12 422.00 partyid Obs Rank Sum

Kruskal-Wallis equality-of-populations rank test

Graficando las medias

Las medianas estn en la misma relacin

como las medias con los demcratas cuya

mediana es 8.5, seguidos por los

independientes con 7, mientras que

republicanos y no involucrados tienen los

menores valores (4.5)

Caso 3.

Con la base ANOVA 2

1. codebook, compact

0 2 4 6 8p 50 of stemcell

noninvolved

independent

republican

democrat

Mediana de la posicin por partido respecto a la investigacin de las clulas madre Los resultados

coinciden con los

resultados de la

tabla Kruskal-

Wallis.

2. Desarrolle el modelo ANOVA

a. Statistics

b. Linear models an related

c. ANOVA/MANOVA

d. One-way ANOVA

e. En la pestaa main:

3. En la pestaan by if/in restrinja la muestra para aquellos que estn entre los 30 y 59 aos

y tienen trabajo de tiempo completo

4. Oprima OK

Aquellos adultos que se mudan a diferentes estados alcanzan

3.06 puntos ms en el indicador de prestigio que el promedio que

permanece en la misma ciudad. Mientras que los que se

mudaron dentro del mismo estado tienen 4.56 puntos mas. Para

el caso de misma ciudad vs diferente las diferencias no son

significativas ya que el valor de la probabilidad es mayor a 0.05

(0.487)

ANOVA de dos factores.

Se tienen dos variables cualitativas que actan como predictores. Usando por ejemplo la relacin

entre prestigio (prestige) y movilidad (mobile16) vara con base en el gnero (sex) del encuestado.

1. Hay que probar si hay relacin entre prestigio y movilidad.

2. Probar su el prestigio est influenciado por el gnero.

3. Verificar si hay un efecto de interaccin, es decir cuando el efecto de una variable, por

ejemplo movilidad, est supeditada a otra, como el gnero.

Procedimiento en stata

1. Statistics 2. Summaries, tables and test 3. Tables 4. One/two-way table of summary statistics

En la pestaa by if/in, incluya las siguientes condiciones:

age>29 & age

Para verificar si las diferencias son significativas, es necesario seguir la siguiente ruta

1. Statistics 2. Linear models and related 3. ANOVA/MANOVA 4. Analysis of variance and covariance

a. Dependent variabel: perstg80 b. Model: mobile16 sex sex#mobile16

Lo que implica que hay tres hiptesis La movilidad tienen un efecto

El gnero influye

La columna de total muestra que la media del

prestigio va de 44.12 a 48.67 y finalmente a

47.19 dependiendo del grado de movilidad de

la persona que responde a la encuesta.

Tambin se ve afectado por el gnero, con las

mujeres, tiene mayor peso el prestigio que en

el caso delos hombres. La media del prestigio

para las mujeres es 47.01 mientras que para

lo hombres es de 45.91.

La interaccin entre movilidad y gnero (sex#mobile16) tiene efectos

En la pestaa by/if/in: age>29 & ageF, si es menor a 0.005, significa que

cada una de las variables es significativa,

en nuestro ejemplo solo se cumple para

mobile16 (movilidad).

2. Variable: mobile16

f. En la pestaa if/in, escriba la condicin age>29 & age29 & age

La lnea azul corresponde con la primera condicin sex==1, es decir a los hombres y la segunda a las mujeres (sex==2). Lo que se puede modificar con el editor de grficas

Las mujeres tienen mayor prestigio que los hombres, respecto a la movilidad, pero hay que ser cauteloso porque las diferencias no son significativas. Las diferencias entre los gneros son mayores cuando se observa a quienes se han mudado de diferentes ciudades, pero an viven en su estado de origen. Tarea Con la base Tarea ANOVA, desarrolle lo que se pide

1. El tiempo que una mujer observa la TV (tvhours) varia dependiendo de su estado civil (MARITAL)? Haga un ANOVA de un factor, incluyendo la tabla de las medias, la comparacin de Bonferri multiple-comparison y presente una grfica de barras que

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1 1.5 2 2.5 3GEOGRAPHIC MOBILITY SINCE AGE 16

Linear Prediction Linear Prediction

Movilidad y prestigio por gnero

SAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITY

SAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITY

DIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATE

SAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITYSAME CITY

SAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITYSAME ST,DIF CITY

DIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATEDIFFERENT STATE

44

46

48

50

Lin

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redic

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1 1.5 2 2.5 3GEOGRAPHIC MOBILITY SINCE AGE 16

Hombres Mujeres

Movilidad y prestigio por gnero

muestre las medias de las horas que pasan viendo la TV por estado civil. Explique los patrones de las medias y las diferencias de las medias.

2. Desarrolle la prueba de Kruskal-Wallis y compare los resultados que obtenga con los resultados obtenidos en el punto 1.

3. Como condicin, considere a las mujeres entre 25 y 40 aos, que trabajan tiempo completo