Intervalo de confianza

Transcription

Intervalo de confianza
Chapter 5
Sampling
Distributions
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Section 5.1
Basic Ideas
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Tipos de Muestra
• Para tomar decisión de la sección estudiada.
– Accesible: Son los datos que se encuentran al alcance del
investigador.
– Experiencia: Son los datos seleccionados por la experiencia
del investigador
• Para tomar decisión de toda la población.
– Aleatoriamente: Cada individuo tuvo la misma oportunidad
de ser seleccionado.
Tipos de Muestreo
• Aleatorio Simple: Conociendo la cantidad de muestras
requeridas se utilizan número aleatorios para seleccionar los
datos de estudio.
• Estratificado: Se sub-divide la población por características de
interés en al menos dos sub-poblaciones (estratos), luego se
realiza un muestreo aleatorio simple.
• Conglomerado “Cluster”: Se divide la población en secciones
o conglomerados, luego se realiza una selección aleatoria de los
conglomerados y se estudian todos sus constituyentes.
Tipos de Muestreo
Cont
• Conveniencia: Se utiliza los resultados que ya están disponibles.
• Sistemáticos: Se selecciona un punto de partida y luego
seleccionamos el enésimo elemento de la población.
Gráfica de Muestras Agrupadas
• Comportamiento de datos:
– Histogramas
– Polígonos
• Localización de datos:
– Ojivas
• Para poder construir estas gráficas:
–
–
–
–
Tenemos que organizar los datos en forma ascendente.
Determinar los intervalos de las clase.
Organizamos los datos en cada clase.
Calculamos la: frecuencia, frecuencia relativa, frecuencia acumulada.
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Section 5.2
The Sample
Mean
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Section 5.3
Illustration of the
Central Limit
Theorem
(Optional)
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Section 5.4
The Normal
Approximation to
the Binomial
Distribution
(Optional)
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Chapter 6
Confidence
Intervals
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Section 6.1
Statistical
Estimation
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Section 6.2
Standard Error of
the Mean
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Section 6.3
Confidence
Interval for m
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Section 6.4
Planning a Study
to Estimate m
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Section 6.6
Comparing Two
Means
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Section 6.7
Confidence
Interval
for (m1 – m2)
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Section 6.8
Perspective and
Summary
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