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Simulation Modeling and Statistical Hypothesis Testing
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Simulation Modeling and Statistical Hypothesis Testing

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Questions and Answers

Cul es el nombre del tipo de simulacin que implica la modelizacin de sistemas con eventos discretos como llegadas y salidas?

  • Simulacin de Monte Carlo
  • Dinmica de sistemas
  • Simulacin de eventos discretos (correct)
  • Modelado basado en agentes
  • Cul es el propsito de la verificacin en la validacin de modelos?

  • Comprobar la precisin del modelo en sistemas reales
  • Realizar un anlisis de sensibilidad del modelo
  • Revisar la lgica interna y la consistencia del modelo (correct)
  • Evaluar la relevancia del modelo en relacin con sistemas reales
  • Cul es el nombre del error que se comete al rechazar la hiptesis nulla cuando es verdadera?

  • Error de tasa de error
  • Error de medicin
  • Error tipo I (correct)
  • Error tipo II
  • Cul es el propsito de la generacin de datos en el anlisis de datos simulados?

    <p>Generar datos para ser utilizados en la simulacin</p> Signup and view all the answers

    Cul es el nombre de la prueba utilizada para comparar la igualdad de varianzas entre dos o ms grupos?

    <p>Prueba de varianza</p> Signup and view all the answers

    Cul es el nombre de la prueba utilizada para comparar la media de una muestra con una media poblacional conocida?

    <p>Prueba de medias</p> Signup and view all the answers

    Cul es el nombre del tipo de simulacin que implica la modelizacin de sistemas complejos con retroalimentacin y stocks?

    <p>Dinmica de sistemas</p> Signup and view all the answers

    Cul es el propsito de la validacin en lamodelizacin?

    <p>Evaluar la relevancia del modelo en relacin con sistemas reales</p> Signup and view all the answers

    Cul es el nombre de la prueba utilizada para comparar la media de dos muestras relacionadas?

    <p>Prueba t de muestras relacionadas</p> Signup and view all the answers

    Cul es el nombre del tipo de simulacin que implica la modelizacin de sistemas con agentes autnomos?

    <p>Modelado basado en agentes</p> Signup and view all the answers

    Study Notes

    Simulation Modeling

    • Simulation Techniques:
      • Monte Carlo simulations: repeated random sampling to estimate outcomes
      • Discrete-event simulations: modeling systems with discrete events (e.g., arrivals, departures)
      • System dynamics: modeling complex systems with feedback loops and stocks
      • Agent-based modeling: modeling systems with autonomous agents
    • Model Validation:
      • Verification: checking the model's internal logic and consistency
      • Validation: checking the model's accuracy and relevance to real-world systems
      • Face validity: checking if the model's outputs seem reasonable and plausible
      • Sensitivity analysis: testing the model's sensitivity to input parameters

    Statistical Hypothesis Testing

    • Statistical Inference:
      • Null hypothesis (H0): a statement of no significant difference or effect
      • Alternative hypothesis (H1): a statement of significant difference or effect
      • Type I error: rejecting H0 when it is true (false positive)
      • Type II error: failing to reject H0 when it is false (false negative)
    • Analysis of Simulated Data:
      • Data generation: using simulation models to generate data
      • Data analysis: applying statistical methods to analyze simulated data
      • Inference: making conclusions about the population based on the sample data

    Hypothesis Tests

    • T-Test (Prueba de Medias):
      • One-sample t-test: comparing a sample mean to a known population mean
      • Independent samples t-test: comparing the means of two independent samples
      • Paired samples t-test: comparing the means of two related samples
    • Variance Test (Prueba de Varianza):
      • Testing the equality of variances between two or more groups
      • F-test: comparing the variances of two groups
    • ANOVA (Prueba de Medias):
      • One-way ANOVA: comparing the means of three or more groups
      • Two-way ANOVA: comparing the means of groups with two factors

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