As part of a Problem Solving Course that I teach, I have several sessions on probability theory. Given that attorneys must frequently make decisions in environments of uncertainty, probability can be a useful skill for law students to learn.

Conditional probability, and Bayes’ Theorem, are important sub-topics that I focus upon. In teaching my students about Conditional Probability, it is often helpful to create a*Conditional Probability Tree*diagram like the one pictured below (sometimes called a probability tree). I’ll explain in a future post why such a diagram/graph is a useful visualization for learners.(See also this Javascript Conditional Probability Tree Diagram webpage that I created in that I describe in a different post.)

**Conditional Probability Tree Diagram**

## No Probability Tree Diagrams in R ?

Like many others, I use the popular free, and open-source R statistical programming language. R is one of the top computing platforms in which to perform machine learning and other statistical tasks (along with Python – another favorite of mine). To program in R, I use the excellent R-Studio application which makes the experience much better.

Given the relationship between R and statistics, I was somewhat surprised that I was unable to find any easily accessible R code or functions to create visually appealing Conditional Probability Tree diagrams like the one above.Thus, I put together some basic R code below for visualizing conditional probability trees, using the Rgraphviz R package. You must install the Rgraphviz package before using the R code below. If you know of other ways to create visually appealing conditional probability tree in R that I may have missed in my search, please let me know.I thought I’d release the code below to others in case it is useful.(Caveat: This is rough code, and has not been thoroughly tested, and is just meant as a starting example to help make your own probability tree diagrams – so no guarantees).(You can also look at this other post about creating a Probability Tree Diagram Using Javascript and D3 if R is not your preferred platform.)**R Code to Create a Visual Conditional Probability Tree**

# R Conditional Probability Tree Diagram # The Rgraphviz graphing package must be installed to do this require("Rgraphviz") # Change the three variables below to match your actual values # These are the values that you can change for your own probability tree # From these three values, other probabilities (e.g. prob(b)) will be calculated # Probability of a a<-.01 # Probability (b | a) bGivena<-.99 # Probability (b | ¬a) bGivenNota<-.10 ###################### Everything below here will be calculated # Calculate the rest of the values based upon the 3 variables above notbGivena<-1-bGivena notA<-1-a notbGivenNota<-1-bGivenNota #Joint Probabilities of a and B, a and notb, nota and b, nota and notb aANDb<-a*bGivena aANDnotb<-a*notbGivena notaANDb <- notA*bGivenNota notaANDnotb <- notA*notbGivenNota # Probability of B b<- aANDb + notaANDb notB <- 1-b # Bayes theorum - probabiliyt of A | B # (a | b) = Prob (a AND b) / prob (b) aGivenb <- aANDb / b # These are the labels of the nodes on the graph # To signify "Not A" - we use A' or A prime node1<-"P" node2<-"A" node3<-"A'" node4<-"A&B" node5<-"A&B'" node6<-"A'&B" node7<-"A'&B'" nodeNames<-c(node1,node2,node3,node4, node5,node6, node7) rEG <- new("graphNEL", nodes=nodeNames, edgemode="directed") #Erase any existing plots dev.off() # Draw the "lines" or "branches" of the probability Tree rEG <- addEdge(nodeNames[1], nodeNames[2], rEG, 1) rEG <- addEdge(nodeNames[1], nodeNames[3], rEG, 1) rEG <- addEdge(nodeNames[2], nodeNames[4], rEG, 1) rEG <- addEdge(nodeNames[2], nodeNames[5], rEG, 1) rEG <- addEdge(nodeNames[3], nodeNames[6], rEG, 1) rEG <- addEdge(nodeNames[3], nodeNames[7], rEG, 10) eAttrs <- list() q<-edgeNames(rEG) # Add the probability values to the the branch lines eAttrs$label <- c(toString(a),toString(notA), toString(bGivena), toString(notbGivena), toString(bGivenNota), toString(notbGivenNota)) names(eAttrs$label) <- c(q[1],q[2], q[3], q[4], q[5], q[6]) edgeAttrs<-eAttrs # Set the color, etc, of the tree attributes<-list(node=list(label="foo", fillcolor="lightgreen", fontsize="15"), edge=list(color="red"),graph=list(rankdir="LR")) #Plot the probability tree using Rgraphvis plot(rEG, edgeAttrs=eAttrs, attrs=attributes) nodes(rEG) edges(rEG) #Add the probability values to the leaves of A&B, A&B', A'&B, A'&B' text(500,420,aANDb, cex=.8) text(500,280,aANDnotb,cex=.8) text(500,160,notaANDb,cex=.8) text(500,30,notaANDnotb,cex=.8) text(340,440,"(B | A)",cex=.8) text(340,230,"(B | A')",cex=.8) #Write a table in the lower left of the probablites of A and B text(80,50,paste("P(A):",a),cex=.9, col="darkgreen") text(80,20,paste("P(A'):",notA),cex=.9, col="darkgreen") text(160,50,paste("P(B):",round(b,digits=2)),cex=.9) text(160,20,paste("P(B'):",round(notB, 2)),cex=.9) text(80,420,paste("P(A|B): ",round(aGivenb,digits=2)),cex=.9,col="blue")

**Another Probability Tree Example in Light Blue with (¬ sign)**