chapter 10 p4 Flashcards
Standard deviation
The standard deviation is a measure of how spread out the data is.
The greater the standard deviation is, the greater the spread of the data. In terms of variation, a characteristic which has a high standard deviation has a large amount of variation.
When you calculate the standard deviation of data that display a normal distribution you will generally find that:
Other statistical tests:
Several statistical tests can be used by scientists to determine the significance of data collected.
These tests can be used in a number of situations, for example when comparing variation within populations, or when comparing the effects of abiotic and biotic factors on organisms
These tests can be used in a number of situations, for example when comparing variation within populations, or when comparing the effects of abiotic and biotic factors on organisms (Chapter 11, Biodiversity).
These include:
Student’s test - this is used to compare the means of data values of two populations
Spearman’s rank correlation coefficient - this is used to consider the relationship of between two sets of data.
Student’s t test:
Student’s t test is used to compare the mean values of two sets of data.
To use this test the data collected must be normally distributed and enough data should be collected to calculate a reliable mean.
Different sample sizes may be used
A significant difference at p = 0.05 means
that if the null hypothesis were correct (i.e., the samples or treatments do not differ) then we would expect to get at value as great as this on exactly 5% of occasions.
You can therefore be reasonably confident that the samples do differ from one another, but there is still nearly a 5% chance of this conclusion being wrong
If the calculated t value exceeds the tabulated value for p = 0.01
then there is a 99% chance of the means being significantly different (and a 99.9% chance if the calculated t value exceeds the tabulated value for p = 0.001).
By convention, a difference between means at the 95% level is
‘significant’, a difference at 99% level is ‘highly significant’ and a difference at the 99.9% level is ‘very highly significant’.
Spearman’s rank correlation coefficient:
If two sets of data are related they are said to be correlated. Iwo sets of data can show:
no correlation
positive correlation
negative correlation
no correlation
no relationship between the data
positive correlation
as one set of data increases in value, the other set of data also increases in value
negative correlation
as one set of data increases in value, the other set of data decreases in value
spearman’s rank formula