Suppose a forester wants to estimate of the average size of the trees in her local park. She already has a data set that contains the unique identification number, species identity, and location for each of the 1000 trees in the park. She decides to estimate the trunk diameter of the population from a sample of trees. She identifies five different methods of sampling the trees. Match the sampling method to each of the following descriptions. a. She divides the data set into five groups, one for each species of tree in the park. She then randomly selects 10 trees to measure from each group.
b. She measures 50 trees that are closest to the parking lot.
c. She sorts the data set by tree identification code. She uses a random number generator to select the first tree to measure. She then selects every 30th tree in the data set until her sample contains 50 trees.
d. She sorts the data set by location and then gives each tree a unique number ranging from 1 to 1000. She selects the trees to measure by creating a list of 50 randomly generated numbers between 1 and 1000
e. She divides the park into 10 rectangles of equal area. She then selects three of the areas at random and forms her sample from the individuals in those areas.

1. Cluster
2. Convenience
3. Stratified
4. Systematic
5. Simple random