Standard Rate May Apply simply means that if you are charged normally on your phone service for text messages then you'll be charged still for sending the text message that is needed, also. But, that doesn't mean you will be charged for the message if you have UNLIMITED TEXTING.
There maybe an additional fee for your message.
It means it's not free. It means that the standard rates for your cell phone carrier apply. In other words, whatever you normally pay for a text message will be charged.
Standard deviation is a measure of variation from the mean of a data set. 1 standard deviation from the mean (which is usually + and - from mean) contains 68% of the data.
Standard deviation is the variance from the mean of the data.
Standard deviation helps you identify the relative level of variation from the mean or equation approximating the relationship in the data set. In a normal distribution 1 standard deviation left or right of the mean = 68.2% of the data 2 standard deviations left or right of the mean = 95.4% of the data 3 standard deviations left or right of the mean = 99.6% of the data
The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.
"Value added services" but what does this mean. It means that on top of the standard charges you will be charged another fee for the privilege of phoning that number. The amount is uncapped and can be anything. So unless you like getting ripped off do not phone any number that say VAS rates apply!
The Z Value, or Z Score, does not apply to the mean, it is a representation of a piece of data. z = (x-µ)/sigma
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
The mean and standard deviation often go together because they both describe different but complementary things about a distribution of data. The mean can tell you where the center of the distribution is and the standard deviation can tell you how much the data is spread around the mean.
The mean of a distribution is a measure of central tendency, representing the average value of the data points. In this case, the mean is 2.89. The standard deviation, which measures the dispersion of data points around the mean, is missing from the question. The standard deviation provides information about the spread of data points and how closely they cluster around the mean.