A cosmetic company wanted to demonstrate the benefit of using their skincare for dark skin treatments. A sample of six was obtained, and each participant used it for 30 days. After 30 days, the scores were as follows:ParticipantBefore treatmentAfter treatment117222161931921415175121861318Is there any significant difference after 30 days? Use α = 0.05.a.Use paired t-test and there is a difference after 30 days of treatment.b.Use ANOVA test and there is a difference after 30 days of treatment.c.Use Z-test and there is a difference after 30 days of treatment.d.Use 2-sample t-test and there is a difference after 30 days of treatment.
Question
A cosmetic company wanted to demonstrate the benefit of using their skincare for dark skin treatments. A sample of six was obtained, and each participant used it for 30 days. After 30 days, the scores were as follows:ParticipantBefore treatmentAfter treatment117222161931921415175121861318Is there any significant difference after 30 days? Use α = 0.05.a.Use paired t-test and there is a difference after 30 days of treatment.b.Use ANOVA test and there is a difference after 30 days of treatment.c.Use Z-test and there is a difference after 30 days of treatment.d.Use 2-sample t-test and there is a difference after 30 days of treatment.
Solution
Para determinar si hay una diferencia significativa después de 30 días de tratamiento, utilizaremos la prueba t pareada, ya que estamos comparando dos conjuntos de datos relacionados (antes y después del tratamiento) para los mismos participantes.
Paso 1: Formular las hipótesis
- Hipótesis nula (H₀): No hay diferencia significativa en las puntuaciones antes y después del tratamiento.
- Hipótesis alternativa (H₁): Hay una diferencia significativa en las puntuaciones antes y después del tratamiento.
Paso 2: Calcular las diferencias
Primero, calculamos la diferencia entre las puntuaciones antes y después del tratamiento para cada participante.
| Participante | Antes del tratamiento | Después del tratamiento | Diferencia (D) |
|---|---|---|---|
| 1 | 17 | 22 | 5 |
| 2 | 16 | 19 | 3 |
| 3 | 19 | 21 | 2 |
| 4 | 14 | 15 | 1 |
| 5 | 17 | 17 | 0 |
| 6 | 18 | 18 | 0 |
Paso 3: Calcular la media y la desviación estándar de las diferencias
-
Media de las diferencias (D̄):
-
Desviación estándar de las diferencias (s_D):
Paso 4: Calcular el estadístico t
Paso 5: Determinar el valor crítico y tomar una decisión
Para un nivel de significancia α = 0.05 y 5 grados de libertad (n-1), el valor crítico de t (bilateral) es aproximadamente 2.571.
- Comparación: |t calculado| < t crítico (2.32 < 2.571)
Conclusión
Dado que el valor calculado de t (2.32) es menor que el valor crítico (2.571), no rechazamos la hipótesis nula. Por lo tanto, no hay evidencia suficiente para afirmar que hay una diferencia significativa en las puntuaciones antes y después del tratamiento.
La respuesta correcta es: a. Use paired t-test and there is a difference after 30 days of treatment.
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