The variance value of 3.65 indicates the degree of dispersion of a dataset around its mean. In a normal distribution, approximately 69% of the data points fall within +/- 1.91 units (the square root of 3.65) of the mean. Variance is defined as the average of the squared distances between each data point and the mean, serving as a measure of data spread similar to standard deviation. The discussion clarifies that the population variance is the square of the population standard deviation.
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Mark44 said:If you're dealing with a normal distribution, it tells you that about 69% of your values are within +/- 3.65 units of the mean.
Mark44 said:If you're dealing with a normal distribution, it tells you that about 69% of your values are within +/- 3.65 units of the mean.
Thanks for the correction. The (population) variance is the square of the (population) standard deviation.mathie.girl said:I thought that in a normal distribution, 69% of your values are within +/- one standard deviation of the mean. So in this case, 68-69% of the data will be in the interval between \mu - \sqrt{3.65} and \mu + \sqrt{3.65}, if your mean is \mu.
Variance is the average of the squares of the distance between your data and the mean. Like standard deviation, it also measures how spread out your data is.