Want this question answered?
When comparing the spread or variability rather than the location or mean. For example, men's heights and women's heights. You "know" that, on average, men will be taller but you may want to see if the variability within the two sets is the same or different.
Used when you have an experiment with several related dependent measures. Also used to analyze data from a within subject design.
The sum of the interior angles is (12-2)*180 = 1800 degrees. But within that constraint, each angle can be anything between (but excluding) 0 and 360 degrees.
3456 (cm)?3 Approximately 14.96 US gallons. When in use, and only filled to within 1 inch of the top, you should treat it as a 13 gallon tank.
The repeated measures design (also known as a within-subjects design) uses the same subjects with every condition of the research, including the control.[1] For instance, repeated measures are collected in a longitudinal study in which change over time is assessed. Other studies compare the same measure under two or more different conditions. For instance, to test the effects of caffeine on cognitive function, a subject's math ability might be tested once after they consume caffeine and another time when they consume a placebo.(Source Reference: - http://en.wikipedia.org/wiki/Repeated_measures )
Sets of data have many characteristics. The central location (mean, median) is one measure. But you can have different data sets with the same mean. So a measure of dispersion is used to determine whether there is a little or a lot of variability within the set. Sometimes it is necessary to look at higher order measures like the skewness, kurtosis.
The range, inter-quartile range (IQR), mean absolute deviation [from the mean], variance and standard deviation are some of the many measures of variability.
minimizes the within-class variability while at the same time maximizing the between-class variability.
The manner in which members of a population are arranged in a particular area is know as dispersion. There are three main kinds of dispersion, which are clumped dispersion, random dispersion, and uniform dispersion.
True
stabilizing
Subject-to-subject differences in within-subjects F refer to the variability in the data between different participants in a study. This difference can impact the within-subject F-value, which measures the effect of a factor within subjects while accounting for individual differences. High subject-to-subject differences can lead to a larger within-subject F-value, indicating a stronger effect of the factor being studied.
It is a diversification of traits within a species. An example of this is ladybugs with different numbers of spots.
Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.Some measures:Range,Interquartile range,Interpercentile ranges,Mean absolute deviation,Variance,Standard deviation.
It doesn't... S. Fimicola is used as an example for crossing over.
S. Gilham has written: 'Dispersion of releases of hazardous materials within buildings'
There are both London Dispersion forces and Dipole-Dipole forces within Acetone.