Variance and standard deviation are two fundamental statistical measures used to quantify the spread or dispersion of a set of data points around their mean (average) value. They indicate how much the data points differ from the mean, giving insight into the distribution's consistency or variability. Variance measures the average squared deviation of each number from the mean of a data set. It gives a sense of the data's spread and is calculated by taking the mean of the squared differences between each data point and the mean of the data set. Standard deviation is the square root of the variance and provides a measure of the dispersion of data points in the same units as the data itself, making it more interpretable than variance. It indicates how much on average the data points deviate from the mean. Problem: In a publication, the observed mean weight of 200 patients was reported as 69.4 ±9.3 kg. If 9.3 kg is the SEM (standard error of mean), calculate the SD (standard deviation) and variance? A) kg / 17298 kg * B) 78.7 kg / 9.3 kg C) kg / 69.4 kg D) 69.4 kg / 131 kg
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