Yes, although the z-scores associated with p-values of 0.01 and 0.05 have special significance, perhaps mostly for historical reasons, all possible z-scores from negative infinity to positive infinity have meaning in statistical theory and practice.
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s is the standard deviation of a sample. It is difficult to know what you are asking. I will note that there is a statistical programming language called S-Plus, see "Modern Applied Statistics with S-Plus, by Venables and Ripley. I also note that "s" is also used commonly in statistics as standard deviation of a sample. That's about all that comes to mind.
Z-scores, t-scores, and percentile ranks are all statistical tools used to understand and interpret data distributions. Z-scores indicate how many standard deviations a data point is from the mean, allowing for comparison across different datasets. T-scores, similar in function to z-scores, are often used in smaller sample sizes and have a mean of 50 and a standard deviation of 10, facilitating easier interpretation. Percentile ranks, on the other hand, express the relative standing of a score within a distribution, showing the percentage of scores that fall below a particular value, thus providing a different type of comparison.
All statistics are data because all statistics are formed of numbers and numbers are a type of data (numrical). But not all data is statistics because not all data is numbers, it can also be words, pictures etc. It's like saying all apples are fruit but all fruit are not apples.
Inter-quartile range, other percentile ranges, mean absolute variation, variance, standard error, standard deviation are all possible measures.
Nearly all the values in a sample from a normal population will lie within three standard deviations of the mean. Please see the link.