Regression Question

[#1]

I have a randomized complete block design. I have 2 treatments (A and B). I have 3 blocks of each treatment (A1, A2, A3 and B1, B2, B3). Within each block I have 15 plots. Within the 15 plots I collected data each time I found one of 3 different types of bushes (M, E, and R) in my plots. I need to run an analysis that will tell me if treatments A and B have a significantly different number of Bushes 1, 2, and/or 3). My data looks like a row for each individual bush with a column for treatment (B or U), a column for block(A1, A2, A3, B1, B2, or B3), a column for plot # (1-15), and a column for the bush type (M, E, or R)  Any help would be really appreciated! I am a novice at stats so the more detail the better. 

A sample of my data is below, but I have it for 398 bushes:

[#2]

How did you design this experiment if you didn't know the regression model, to begin with?

What is a Block? Is just replication? What is Plot? It seems like Block and Plot are not factors, but just define a grid for a sampling plan. Are they physically distinct locations with different qualities (e.g., soil type, rain fall)?

[#3]

Fair questions for sure. I am very new to stats and had help designing my experiment. Yes, block is just replication. Plot is a 10 by 10 meter area in which I recorded all bushes of the 3 types. So another way of putting it is: I have 2 treatments (A and B) with 3 replications of each treatment (A1, A2, A3, B1, B2, B3), within each replication are 15 individual plots for a total of 90 plots, within each plot I record each bush as either E, R, or M. Each row of data is 1 single bush.

[#4]

It seems that Block and Plot are both replicates for sampling. What is the difference between them? How is a block formed? How is a plot formed? How is the treatment applied to a plot?