It is a statistical measure that helps you understand the sample/population data.
For a sample of data it is a measure of the spread of the observations about their mean value.
perameter is a measure of population or universe, statistic is a measure of a sample data drawn from population
Data gathering in two different samples such that there is matching of the first sample data drawn and a corresponding data value in the second sample.
I've included a couple of links. Statistical theory can never tell you how many samples you must take, all it can tell you the expected error that your sample should have given the variability of the data. Worked in reverse, you provide an expected error and the variability of the data, and statistical theory can tell you the corresponding sample size. The calculation methodology is given on the related links.
It is impossible to determine the percentiles if you are given only the sample mean since percentiles are a measure of the spread of the data; the mean gives no information on that.
It is a statistical measure that helps you understand the sample/population data.
A 99.6 percentile means that 99.6% of the data in the sample is at or below the data point given.
For a sample of data it is a measure of the spread of the observations about their mean value.
perameter is a measure of population or universe, statistic is a measure of a sample data drawn from population
Data is neither sample nor population. Data are collected for attributes. These can be for a sample or a population.
Data gathering in two different samples such that there is matching of the first sample data drawn and a corresponding data value in the second sample.
there is a matching of the first sample data drawn and a corresponding data value in the second sample data.
I've included a couple of links. Statistical theory can never tell you how many samples you must take, all it can tell you the expected error that your sample should have given the variability of the data. Worked in reverse, you provide an expected error and the variability of the data, and statistical theory can tell you the corresponding sample size. The calculation methodology is given on the related links.
In general when you take a sample of values of a random variable you will find that those values lie around some central value that is characteristic of the total population for the random variable. A measure of central tendancy (such as a sample mean, sample mode or sample median) is a statistic which is intended to estimate the central value of the population using the values in the sample in some way.
Because it is in same units as the original data. For example, if you have a sample of lengths, all in centimetres, the sample variance will be in units of centrimetres2 which might be more difficult to interpret but the sample standard deviation with be in units of centimetres, which would be relatively easy to intepret with reference to the data.
Sample Bio-Data Form