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# Time for action – visualizing the likelihood function

We will now visualize the likelihood function for the binomial, Poisson, and normal distributions discussed before:

1. Initialize the graphics windows for the three samples using `par(mfrow= c(1,3))`.
2. Declare the number of trials n and the number of success x by `n <- 10; x <- 7`.
3. Set the sequence of p values with `p_seq <- seq(0,1,0.01)`.

For `p_seq`, obtain the probabilities for n = 10 and x = 7 by using the `dbinom` function: `dbinom(x=7,size=n,prob=p_seq)`.

4. Next, obtain the likelihood function plot by running `plot(p_seq, dbinom( x=7,size=n,prob=p_seq), xlab="p", ylab="Binomial Likelihood Function", "l")`
5. Enter the data for the Poisson random sample into R using `x <- c(1,2,2,1, 0,2,3,1,2,4)` and the number of ...

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