I repeated this 1'000 times. Here they are all in the same plot: 8 8 value o -100 200 400 600 800 1000 time Here is a histogram of the values each run landed on at the last iteration (step 1000): histogram of endpoints 100 Frequency 150 50 100 -100 -50 -150 ending valueQ1: In common usage (not statistics or biology), does calling a process random make it more or less predictable? How about more or less measurable? Give an example in a sentence and bear in mind that there are no wrong answers, except a blank answer. Q2: In this simulation experiment, why did we not get exactly the same value for each random walk? What was the source of the variation? Q3: Does the presence of variation mean that the system cannot be described mathematically? Does it mean the random walk is unpredictable? Explain. Q4: What do you think would happen to the histogram ofthe value at the last iteration if we ran 10'000 repetitions instead of 1000? What if we only built the histogram from 50 repetitions? In the following figures, I have simulated what is known as a random walk. The way this works is as follows: I start with a value of 0. I am going to track the sum of values as I increment forward. At every iteration, I flip a coin. If I get heads, I add a value of 1, and if I get tails, I add a value of -1. I do this for 1000 iterations. Here is what that looks like: 8 8 8 -100 200 400 800 1000 Now, I repeated the same procedure 6 independent times: -160 -50 -150 -160 60 -150 800 1000 200 800 200 800 60 100 80 100 -160 40 -160 50