Suddenly, it's not clear that there's an important difference in age between these two groups. This time the average age for those with an IV is 9.2 years and the average age for those without an IV is 8.9 years, for a difference of 0.3 years. Now suppose you collect the same data over the next six weeks. From this, you might conclude that those receiving an IV were older on average. The difference between the two means is 1.9 years. You review the ambulance runs for the past two weeks and calculate a mean age of 10.4 years for those with an IV and 8.5 years for those without an IV. Suppose that you want to compare the mean age for those with and without an IV in the prehospital setting. Each sample you take will give you a different result. When you calculate a statistic based on your sample data, how do you know if the statistic truly represents your population? Even if you've selected a random sample, your sample will not completely reflect your population. In cases where the standard deviation of an entire population cannot be found, it is estimated by examining a random sample taken from the population and computing a statistic of the sample.Remember that there is variability associated with your outcomes and statistics. \displaystyle \text, is a statistic known as an estimator. The mid-range of a set of statistical data values is the arithmetic mean of the maximum and minimum values in a data set, defined as: However, because the information the range provides is rather limited, it is seldom used in statistical analyses.įor example, if you read that the age range of two groups of students is 3 in one group and 7 in another, then you know that the second group is more spread out (there is a difference of seven years between the youngest and the oldest student) than the first (which only sports a difference of three years between the youngest and the oldest student).
This can be useful when comparing similar variables but of little use when comparing variables measured in different units. The range is measured in the same units as the variable of reference and, thus, has a direct interpretation as such. The range is interpreted as t he overall dispersion of values in a dataset or, more literally, as the difference between the largest and the smallest value in a dataset. Unlike other more popular measures of dispersion, the range actually measures total dispersion (between the smallest and largest values) rather than relative dispersion around a measure of central tendency. In statistics, the range is a measure of the total spread of values in a quantitative dataset. dispersion: the degree of scatter of data.range: the length of the smallest interval which contains all the data in a sample the difference between the largest and smallest observations in the sample.
The mid-range of a set of statistical data values is the arithmetic mean of the maximum and minimum values in a data set.Because the information the range provides is rather limited, it is seldom used in statistical analyses.