Any variation is very sensitive to extreme values!
Chat with our AI personalities
false
Median cannot be used for qualitative data (a mode can).The sampling distribution of the median is complicated (the mean is well studied).Median can usually be used for data that can be ordered without there being a ratio scale. For example, "small-medium-large", or "very negative-negative-neutral-positive-very positive". A mean cannot be calculated without arbitrarily assigning a numerical value to the terms.A median is not dependent on all the values which means that it is not distorted by outliers (extreme values).It is easy to find the median value from cumulative frequency charts.
Standard index form is a convenient way to represent very large or very small numbers. It is often used in physics where these extreme values are used regularly. E.g. 6.63 x 10-34 is a common value used. 5 x 102 is 500 which is equivalent to 5 x 10 x 10 5 x 10-2 is 0.05 which is equivalent to 5 / 10 / 10
W The test statistic is is the critical region or it exceeds the critical level. What this means is that there is a very low probability (less than the critical level) that the test statistics could have attained a value as extreme (or more extreme) if the null hypothesis were true. In simpler terms, if the null hypothesis were true you are very, very unlikely to get such an extreme value for the test statistic. And although it is possible that this happened purely by chance, it is more likely that the null hypothesis was wrong and so you reject it.
It´s a system that forces to zero values smaller than a given value. This is done in order to avoid measure or report very small values seen as noises.