The discussion revolves around the interpretation of a calculated variance value of 3.65 from a set of measurements. Participants are exploring the implications of this variance in the context of statistical distributions, particularly normal distribution.
There is an ongoing exploration of the implications of the variance value, with some participants providing clarifications regarding the relationship between variance and standard deviation. Multiple interpretations of the statistical properties are being discussed, but no consensus has been reached.
Participants are operating under the assumption that the data follows a normal distribution, which is central to their interpretations of the variance value. There is also a mention of the distinction between population variance and sample variance.
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 [tex]\mu - \sqrt{3.65}[/tex] and [tex]\mu + \sqrt{3.65}[/tex], if your mean is [tex]\mu[/tex].
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.