Data Distribution Assignment

Background:

There are many different kinds of distributions for sample data.Problably the most common distribution is the normal distribution. When data are normally distributed, they fit a "bell-curve". A special case of the normal distribution is the Poisson Distribution. It is applicable when sample size is small. Both the Poisson and normally distributed data are easy to work with in a statistical sense and one usually hopes that collected data will fit one or the other. If the data doesn't fit either distribution, there are techniques to work with it, but they are more complicated.

Directions:

1. Use the data that was collected for the acorn and pine cone study. Sample size was small and numbers of individuals per sample were also small. You can either use numbers or biomass values. You will have to divide the numbers of individuals or biomass per sample into six or seven categories and retabulate the data in order to make sense of it.

2. Plot the data so that the x-axis represents the categories (i.e., numbers of individuals or biomass per area sampled) and the y-axis represents the number of samples that fit into each category.

3. Calculate a theoretical Poisson Distribution for the data set.

4. Plot that distribution on the same graph that you have plotted the observed distribution on.

5. Calculate the Chi-square value for the differences between the observed and theoretical distributions. Determine whether the two distributions are the same statistically.

6. Turn in for credit the graph and a result/discussion page that provides the chi-square value and a brief discussion of your findings.