standard deviation is 1 what does it mean
Standard deviation The standard deviation of a random variable, statistical population, data set, or probability distribution is the square root of its variance. It is algebraically simpler, though in practice less robust, than the average absolute deviation.[2][3] A useful property of the standard deviation is that, unlike the variance, it is expressed in the same units as the data. There are also other measures of deviation from the norm, including average absolute deviation, which provide different mathematical properties from standard deviation.[4]
Mean The mean of a probability distribution is the long-run arithmetic average value of a random variable having that distribution. In this context, it is also known as the expected value. For a discrete probability distribution, the mean is given by   ∑ x P ( x )  {\displaystyle \textstyle \sum xP(x)} , where the sum is taken over all possible values of the random variable and   P ( x )  {\displaystyle P(x)}  is the probability mass function. For a continuous distribution,the mean is    ∫ − ∞  ∞  x f ( x ) d x  {\displaystyle \textstyle \int _{-\infty }^{\infty }xf(x)\,dx} , where   f ( x )  {\displaystyle f(x)}  is the probability density function. In all cases, including those in which the distribution is neither discrete nor continuous, the mean is the Lebesgue integral of the random variable with respect to its probability measure. The mean need not exist or be finite; for some probability distributions the mean is infinite (+∞ or −∞), while others have no mean.