Name: measuring error in scientific data
Uploaded: 2023-09-22T11:49:39.000Z
Duration: 1 min 20 s
Channel: JoVE

Los errores en el proceso de medición son un problema común. Estos errores pueden clasificarse en dos categorías: aleatorios y sistemáticos.
Los errores aleatorios son el resultado de inconsistencias en el proceso de medición o variaciones en la cantidad que se mide. Esto da lugar a fluctuaciones, demasiado altas o demasiado bajas, en torno al valor real.
Considere a un científico que mide la longitud de una lombriz de tierra usando un calibrador. La inconsistencia del científico para leer las escalas correctamente, o el movimiento continuo del cuerpo de la lombriz de tierra durante la medición, puede resultar en mediciones de longitud incorrectas.
El error aleatorio no se puede evitar, sin embargo, se puede promediar con intentos repetidos.
Los errores sistemáticos son el resultado de un problema persistente y conducen a una discrepancia constante en la medición. Estos errores tienden a ser demasiado altos o demasiado bajos en comparación con el valor real. Por ejemplo, pesos que se miden utilizando una balanza de pesaje mal calibrada.
Estos son predecibles y en su mayoría están relacionados con instrumentos. Sin embargo, a diferencia del error aleatorio, no se puede promediar con mediciones repetidas.

errores aleatorios y sistemáticos

Los científicos siempre intentan registrar las mediciones con la máxima precisión y exactitud. Sin embargo, a veces ocurren errores. Estos errores pueden ser aleatorios o sistemáticos. Los errores aleatorios se observan debido a la inconsistencia o fluctuación en el proceso de medición, o a las variaciones en la magnitud misma que está siendo medida. Tales errores fluctúan entre ser mayores o menores que el valor real en mediciones repetidas. Considere a un científico midiendo la longitud de una lombriz de tierra usando una regla. El error aleatorio en este proceso de medición puede ser el resultado del método inconsistente en el que el científico lee las escalas, o si la lombriz de tierra se está moviendo. El error aleatorio no se puede evitar; sin embargo, se puede promediar con ensayos repetidos. Los errores sistemáticos surgen de un problema persistente y resultan en una discrepancia constante en la medición. Estos errores tienden a ser consistentemente mayores o menores que el valor real. Son predecibles y en su mayoría son de naturaleza instrumental. Por ejemplo, una balanza de pesaje incorrectamente calibrada puede pesar consistentemente objetos más pesados que su valor real. A diferencia del error aleatorio, los errores sistemáticos no se pueden promediar con mediciones repetidas. Este texto está adaptado de <a href="https://openstax.org/books/chemistry-2e/pages/1-5-measurement-uncertainty-accuracy-and-precision">Openstax, Chemistry 2e, Sección 1.5: Incertidumbre de medición, exactitud y precisión.</a>

Errores aleatorios y sistemáticos

Los científicos siempre hacen todo lo posible para registrar las mediciones con la máxima exactitud y precisión. Sin embargo, a veces se producen errores. Estos errores pueden ser ...

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Unit 1

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Physics Basics

Conceptos básicos de física

KEY TERMS AND CONCEPTS

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Random and Systematic Errors

measuring error in scientific data

Random and systematic errors affect scientific measurements. Random errors cause values to spread around the true value. They make repeated measurements less consistent. Systematic errors shift measurements in the same direction each time.

Understanding both kinds of error helps students judge data quality. Random error can come from small changes during measurement. Systematic error can come from a biased tool or method. Scientists look for these patterns so they can improve results and interpret data more carefully.

Measuring Error in Scientific Data

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vector or cross product

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Vectors describe quantities that have both size and direction. They are used in physics to show how motion, force, and other quantities act in space. A vector can be represented with an arrow. The length of the arrow shows the size, and the arrowhead shows the direction. This makes vectors useful for comparing how one quantity points relative to another. Scalars are different because they have size only and no direction. Understanding the difference between vectors and scalars is an important...

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accuracy and precision

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rules of significant figures

Counting Significant Figures in Measurements

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random and systematic errors

Random and systematic errors affect scientific measurements. Random errors cause values to spread around the true value. They make repeated measurements less consistent. Systematic errors shift measurements in the same direction each time. Understanding both kinds of error helps students judge data quality. Random error can come from small changes during measurement. Systematic error can come from a biased tool or method. Scientists look for these patterns so they can improve results and...

position and displacement

Tracking Motion with Position and Displacement

Position and displacement are key ideas in straight-line motion. Position tells where an object is located compared with a chosen starting point, called the origin. Displacement describes how far and in what direction the object has moved from its starting position. These ideas help describe motion clearly. Position can change as an object moves. Displacement focuses on the change in position, not just the path taken. That makes it useful for comparing motion in a simple and precise way.

position and displacement vectors

Using Vectors to Describe Motion

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mass and weight

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gravitational force

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key terms and concepts

Learn how random and systematic errors affect scientific measurements, why they matter, and how they change the way students judge data quality.

Measuring Error in Scientific Data | JoVE K12

JoVE Core Mechanical Engineering offers concise, easy-to-understand animated videos covering key topics such as equilibrium, forces, truss analysis, and structural mechanics. Explore their real-world applications, and witness these concepts in action through scientist-led experiments.

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Measuring Error in Scientific Data

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