Name: why control groups improve experiment results
Uploaded: 2023-04-30T12:27:59.000Z
Duration: 1 min 13 s
Channel: JoVE

K12 Standards

Virginia  Standards of Learning

HIgh School

Biology

BIO.1

BIO.1.c

Controls in Experiments

Los controles de un experimento son elementos que se mantienen constantes y no se ven afectados por variables independientes. Los controles son esenciales para la medición imparcial y precisa de las variables dependientes en respuesta al tratamiento.
Por ejemplo, se sospecha que los pacientes que acuden a un hospital con fiebre alta, dificultad para respirar, tos, resfriado y dolor corporal intenso están infectados por COVID. Pero también es posible que otras infecciones respiratorias causen los mismos síntomas. Por lo tanto, el médico recomienda una prueba de COVID.
Se recogen los hisopos nasales del paciente y se realiza la prueba de COVID. Además, se mantiene una muestra de control que no tiene ARN viral COVID. Este tipo de control también se denomina control negativo. Ayuda a prevenir informes de falsos positivos en las muestras de los pacientes.
Un control positivo es otro tipo de control comúnmente utilizado en un experimento. A diferencia del control negativo, el control positivo contiene una muestra real: el ARN viral. Esto ayuda a coincidir con la presencia de ARN viral en las muestras de prueba y valida el procedimiento y la precisión de la prueba.

controles en experimentos

Al realizar un experimento, es fundamental tener control para reducir el sesgo y medir con precisión las variables dependientes. También marca los resultados más fiables. Los controles son elementos de un experimento que tienen las mismas características de los grupos de tratamiento pero que no se ven afectados por la variable independiente. Al clasificar estos datos en condiciones experimentales y de control, se puede establecer la relación entre las variables dependientes e independientes. Un experimento aleatorio siempre incluye un grupo de control que recibe un tratamiento inactivo pero que, por lo demás, es manejado exactamente como los demás grupos. El grupo de control ayuda a los investigadores a equilibrar los efectos de participar en un experimento con los efectos de los tratamientos activos.

En los procedimientos clínicos o de diagnóstico, se incluyen controles positivos para validar los resultados de la prueba. Los controles positivos mostrarían el resultado esperado si la prueba hubiera funcionado como se esperaba. Un control negativo no contiene el ingrediente o tratamiento principal, pero incluye todo lo demás. Por ejemplo, en una prueba COVID RT-PCR, una muestra negativa no incluye el ADN viral. Los experimentos suelen utilizar controles positivos y negativos para prevenir o evitar reportes de falsos positivos y falsos negativos. 

Este texto es una adaptación de <a href="https://openstax.org/books/statistics/pages/1-4-experimental-design-and-ethics">Openstax, Introductory Statistics, Section 1.4, Experimental Design and Ethics.</a>

Controles en experimentos

Al realizar un experimento, es crucial tener control para reducir el sesgo y medir con precisión las variables dependientes. También marca los resultados más ...

Education

Educación

JoVE Core

Statistics

Estadísticas

Unit 1

Unidad 1

Statistics in Practice

Estadística en la práctica

KEY TERMS AND CONCEPTS

TÉRMINOS Y CONCEPTOS CLAVE

why control groups improve experiment results

Control groups help experiments produce more reliable results. They reduce bias and make it easier to measure the dependent variable. In an experiment, controls have the same features as the treatment groups but are not affected by the independent variable.

Researchers sort data into control and experimental conditions to see the relationship between the independent and dependent variables. A randomized experiment includes a control group that receives an inactive treatment. The control group is otherwise managed the same way as the other groups. This helps balance the effects of being in an experiment with the effects of the active treatments.

Controls are also important in clinical and diagnostic tests. Positive controls are used to confirm that a test gives the expected result when it works correctly. A negative control does not include the main ingredient or treatment, but it includes everything else. For example, in a COVID RT-PCR test, a negative sample does not include viral DNA.

Using positive and negative controls can help prevent false positive and false negative reports. These controls make test results more trustworthy and help researchers validate their findings.

Why Control Groups Improve Experiment Results

why-control-groups-improve-experiment-results

what is an experiment?

Random Assignment in Experiments

Random assignment in experiments helps researchers test cause and effect between two variables. An experiment is a planned activity carried out under controlled conditions. It is used to study how one variable affects another. The variable that causes change is the explanatory or independent variable. The variable that changes in response is the response or dependent variable. In a randomized experiment, the researcher changes the explanatory variable and measures the response variable. The...

study design in statistics

Experimental and Observational Study Types

Study design in statistics helps researchers collect and analyze data from variables in a specific research problem. It supports stronger experiments and more reliable data. Questions about aspirin and heart attacks, fertilizer and rose growth, or fatigue and alcohol-related driving risk all depend on careful study design. Study designs are usually grouped into two main types: descriptive and analytical studies. Descriptive studies describe the variables and answer what is happening, rather...

observational studies

Types of Observational Research Methods

Observational research methods let scientists study events without changing them. The researcher does not intervene, so the response variable and the outcome are left alone. These studies are used to look for patterns and relationships in real-world settings. There are three main types of observational studies: prospective, retrospective, and cross-sectional. Each type collects information in a different way. Together, they help researchers answer questions about health, behavior, and risk. <br...

experimental designs

Types of Experimental Design

Experimental design is a systematic way to study how an independent variable affects a dependent variable. Researchers use it to compare results and judge whether a treatment or intervention changes the outcome. Three common experimental designs are pre-experimental design, true experimental design, and quasi-experimental design. Each one supports research in a different way, depending on how groups are formed and how the data are collected. In pre-experimental design, the researcher compares...

randomized experiments

How Random Assignment Reduces Bias

Random assignment helps researchers place participants into experimental and control groups. It gives each person an equal chance of being assigned to either group. This process is used to reduce selection bias and to balance known and unknown confounding factors, so the control group is as similar to the treatment group as possible. A computer program or a random number generator can make the assignment process less biased. Simple randomization is the most direct method. It uses a single...

crossover experiments

Repeated-Measures Study Design

Crossover experiments are a repeated-measurements study design used in science and medicine. In this design, the same experimental units receive all treatments during different time periods. That setup helps compare how each treatment performs within the same group. These studies are used in psychology, the pharmaceutical industry, agriculture, and medicine. They can work with smaller sample sizes because the samples act as their own controls. That makes crossover designs useful when...

controls in experiments

Control groups help experiments produce more reliable results. They reduce bias and make it easier to measure the dependent variable. In an experiment, controls have the same features as the treatment groups but are not affected by the independent variable. Researchers sort data into control and experimental conditions to see the relationship between the independent and dependent variables. A randomized experiment includes a control group that receives an inactive treatment. The control group...

bias

Biased Sampling and Fair Tests

Bias is any tendency that keeps a question from being unprejudiced. In research, bias appears when one outcome or answer is favored over others during sampling or testing. It can happen at many stages, including study design, data collection, analysis, and publication. A common form is sampling bias. This happens when a sample is taken from a population and some members are less likely to be chosen than others. In a fair sample, each member of the population should have an equally likely...

blinding

Placebos and Bias in Randomized Trials

Placebos and blinding are key tools in randomized control trials, or RCTs. They help researchers reduce bias, which can affect study results. In a blinded study, participants do not know which treatment they are receiving. A placebo is a dummy treatment that does not contain the active treatment. Researchers use a placebo in the control group to compare against the treatment group. This helps balance the effects of being in an experiment with the effects of the active treatment itself. A...

clinical trials

How Clinical Trials Test New Treatments

Clinical trials test new treatments in people to check safety and effectiveness. These experimental studies can look at drugs, diet methods, and medical devices. Researchers use statistics to turn collected data into reasonable and accurate conclusions, so they can make sound decisions when results are uncertain. Statistics also help medical researchers reduce error and bias. That matters because clinical trial data can be influenced by chance or by uneven study design. Careful analysis...

key terms and concepts

Learn how control groups, positive controls, and negative controls reduce bias, validate tests, and make experiment results more reliable.

Why Control Groups Improve Experiment Results | JoVE K12

statistics

JoVE Core Estadística presenta a los estudiantes los conceptos y las aplicaciones de la recopilación, análisis, presentación e interpretación de datos. Estas lecciones animadas proporcionan un entendimiento de la estadística a estudiantes de una amplia variedad de disciplinas. Además, los vídeos de científicos en acción muestran la aplicación de los conceptos en experimentos de investigación clásicos y originales, llevados a cabo hoy en día en laboratorios de ámbito internacional.

Chemistry

CH.1

CH.1.c

Physical Science

PS.1

PS.1.b

Physics

PH.1

PH.1.b

Texas Essential Knowledge and Skills

High School

CHEM.1

CHEM.1.B

Georgia Standards of Excellence

9-12

Epidemiology

SEPI3.

SEPI3.c

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organisms, from examining models and theories, and/or to seek additional
information
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school laboratory or field to determine relationships between independent
and dependent variables
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BIO.1.a

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Relative Frequency Histogram

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Multiple Bar Graph

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Pareto Chart

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Arithmetic Mean

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Mean From a Frequency Distribution

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Midrange

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Standard Deviation

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Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in ...

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more ...

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 • use data in building and revising models, supporting an explanation for phenomena, or testing solutions to problems
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Why Control Groups Improve Experiment Results

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