El entrenamiento continuo de intensidad moderada generó una mayor reducción en la presión arterial sistólica, comparado con el de intervalos de gran intensidad (mediana: 8 mm Hg p<0,001). Sin embargo, las diferencias entre grupos no fueron estadísticamente significativas (1,01 ml/kg por minuto IC95% -2,16 a 4,18 p=0,52). El análisis dentro de cada grupo mostró un aumento en el volumen máximo consumido de oxígeno de 3,5 ml/kg por minuto (intervalo de confianza, IC95% 2,02 a 4,93 p=0,0001) con el entrenamiento con intervalos de gran intensidad, y de 1,9 ml/kg por minuto (IC95% -0,98 a 4,82 p=0,18) con el continuo de intensidad moderada. El primer grupo completó 15 cargas de 30 segundos (90-95 % de la frecuencia cardiaca máxima y, el segundo hizo 40 minutos continuos (65-75 % de la frecuencia cardiaca máxima). Ambos grupos hicieron 24 sesiones en tapiz rodante. Se incluyeron 44 voluntarios, 22 a entrenamiento con intervalos de gran intensidad y 22 a uno continuo de intensidad moderada. Se hizo un ensayo clínico controlado con asignación al azar. Máximo consumido de oxígeno (VO2max), la presión arterial sistólica y la presión arterial diastólica, durante ocho semanas en hombres sanos entre los 18 y los 44 años de edad. Comparar los efectos del entrenamiento con intervalos de gran intensidad de bajo volumen y del entrenamiento continuo de intensidad moderada, en el volumen El entrenamiento con intervalos de gran intensidad (High Intensity Interval Training, HIIT) podría causar mayores incrementos en la capacidad cardiorrespiratoria comparado con el entrenamiento continuo de intensidad moderada, aunque la información actual no es concluyente. El ejercicio aeróbico incrementa la capacidad cardiorrespiratoria, considerada como factor de protección frente a enfermedades cardiovasculares. The greater the margin of error is, the wider the interval is, and the less certain you can be about the value of the point estimate.Introducción. For example, the mean estimated length of a camshaft is 600 mm and the confidence interval ranges from 599 to 601. When a confidence interval is symmetric, the margin of error is half of the width of the confidence interval. This means that the true approval rating is +/- 5%, and is somewhere between 50% and 60%.įor a two-sided confidence interval, the margin of error is the distance from the estimated statistic to each confidence interval value. For example, a political poll might report that a candidate's approval rating is 55% with a margin of error of 5%. You probably already understand margin of error as it is related to survey results. The margin of error quantifies this error and indicates the precision of your estimate. When you use statistics to estimate a value, it's important to remember that no matter how well your study is designed, your estimate is subject to random sampling error. Point Estimate This single value estimates a population parameter by using your sample data. The confidence interval is determined by calculating a point estimate and then determining its margin of error. Therefore, they can be 95% confident that the mean length of all pencils is between 50 and 54 millimeters. The manufacturer takes a random sample of pencils and determines that the mean length of the sample is 52 millimeters and the 95% confidence interval is (50,54). For example, a manufacturer wants to know if the mean length of the pencils they produce is different than the target length. Use the confidence interval to assess the estimate of the population parameter. A 95% confidence interval indicates that 19 out of 20 samples (95%) from the same population will produce confidence intervals that contain the population parameter. The red confidence interval that is completely below the horizontal line does not. The vertical blue confidence intervals that overlap the horizontal line contain the value of the population mean. Here, the horizontal black line represents the fixed value of the unknown population mean, µ. But if you repeated your sample many times, a certain percentage of the resulting confidence intervals would contain the unknown population parameter. Because of their random nature, it is unlikely that two samples from a particular population will yield identical confidence intervals. A confidence interval is a range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter.
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