|Tardigrades||Creating the Context: Data Analysis|
Results of Study
Results of Study
So, now that I have my data, what do I do with it?
The methods and number of steps used in gathering scientific knowledge may vary from one investigator to the next, but scientific methods usually involve the alternation of two types of activities, the observational and the explanatory. So far we have been making observations about tardigrades, but we have not yet participated in the explanatory part of science. We can continue to explore the data we have collected so far to increase the accuracy of our observations. The tardigrade data set you have does not really mean very much yet because we do not know whether this data is typical, high, low, or how it compares to "normal".
Statistics refers to a set of procedures and rules for reducing our data sets to manageable proportions and allowing us to take the next step and draw conclusions from our data. Our purpose is to increase the meaning of our observations reflected in our data so we will employ descriptive statistics. The most common numerical way to look at data is by means and extremes. The mean is the sum of the data values divided by the number of data points. In everyday language, this is the average. Extremes deal with how much vaiation from the average you observe. Two common ways to use numbers to compare sites is to use Density and Diversity.
Calculating Tardigrade Density
Density will give us an indication of how many tardigrades we find in a given area. This number will allow us to compare densities between different sites. To calculate the density of tardigrades students should determine the lichen surface area for the sample you are observing. If a round borer was used to collect the lichens, the area of the lichen sample is:
Lichen Area = (3.14)(radius of the sample) 2
Density of the tardigrades is calculated by dividing the number of tardigrades observed by the area of the lichen sample. Density is calculated for each family of tardigrade by dividing the number of each family of tardigrade observed by the total surface area of the lichen.
Tardigrade Density Echiniscidae = Number of tardigrades Echiniscidae/Lichen Area
Calculate the mean density by summing the densities of all the types of tardigrades and dividing by the number of families found.
Mean Density = (Density of Echiniscidae + Density of Oreellidae)/ Number of families found
Calculating diversity using the Simpson Diversity Index
Tardigrade diversity will give us a measure on the number of differnt types of tardigrades we find in a given area. This value can also be compared between sites. Calculate the proportion of the total number of tardigrades of each type (Pi).
Proportion Echiniscidae (Pa) = number of Echiniscidae/Total number
To calculate the Simpson Diversity Index = 1-Sum of [Pi2]
For example, if you looked at 50 tardigrades classified as Echiniscidae and 20 tardigrades of Oreellidae you would calculate:
Diversity Index = 1- ((50/70)2) + (20/70)2)
This index ranges from zero to one and is literally a measure of the probability that two tardigrades taken at random from the sample are different species. A number close to zero means low diversity and it is likely you will get the same species of tardigrade and a number close to one means high diversity and you are likely to get different species from a sample.
Using Geographic Information Systems for Analysis
A geographic information system (GIS) is a computer-based tool for mapping and analyzing things that exist and events that happen on earth. The data that we have collected as a part of this project is well suited to GIS technology because it has a critical geographic dimension. GIS integrates common database operations such as query and statistical analysis with the unique visualization and geographic analysis benefits offered by maps. These abilities distinguish GIS from other types of analysis.
Geographic information systems work with two fundamentally different types of geographic models - the "vector" model and the "raster" model. In the vector model, information about points, lines, and polygons is encoded and stored as a collection of x,y coordinates. The location of a point feature, such as a bore hole, can be described by a single x,y coordinate. Linear features, such as roads and rivers, can be stored as a collection of point coordinates. Polygonal features, such as sales territories and river catchments, can be stored as a closed loop of coordinates.
I would like to work with the data in a map-based format.
|1999, KanCRN Collaborative Research Network|