Discussion post 2: Exploration part 1: In class, we saw the “tossing of two dice” experiment…

Discussion post 2: Exploration part 1: In class, we saw the “tossing of two dice” experiment…
Discussion post 2: Exploration part 1: In class, we saw the “tossing of two dice” experiment simulated in R. The simulation recorded the frequency of an odd number on the first die, an odd number on the second and the frequency of an odd on both. The function ind that simulated the experiment was coded in an script file. The ind function has only one argument: the Size vector. It the example we saw, Size is a vector of length 4 where each entry represents the number of times the two dice are tossed. From the screenshot output below, Size = c(100, 500, 1000), that is, the dice were tossed 100 times, 500 times, and 1000 times. As can be seen under PROGRAM OUTPUT in the screenshot, the sample size has an effect on the relative frequencies. The Error indicates how close the Both Odd percentage is to the (Die1 Odd)*(Die2 Odd) given in column F1*F2 – which is actually how we calculate the probability of two independent events (by multiplying the probability of each). This simulation illustrates a comparison between relative frequency Both Odd from the simulated experiment and the multiplication law for the probability of independent events F1*F2. > Size – CC100,500,1000) > ind(Size) PROGRAM OUTPUT Diel Odd Diez Odd Both Odd F1 F2 Error N= 100 0.540 0.580 0.210 9.27001 – 60000 N 500 0.488 0.518 0.266 0.252784 0.013216 N-1080 0.583 0.476 0.233.239428 -0.006428 2. What is the value of simulating an experiment in R? May 11 2022 01:55 AM

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