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Without specific details about the probability distribution, it is difficult to provide a specific method to compute the cumulative distribution function (CDF) using R. However, in general, R provides built-in functions to compute the CDF for various probability distributions such as normal, binomial, Poisson, exponential, etc.

For example, to compute the CDF of the standard normal distribution up to a value of 1.96, you can use the pnorm() function in R as follows:

pnorm(1.96)

This will give you the probability that a random variable from the standard normal distribution is less than or equal to 1.96.

Similarly, to compute the CDF of a binomial distribution with 10 trials and a probability of success of 0.5 up to a value of 5, you can use the pbinom() function in R as follows:

pbinom(5, size = 10, prob = 0.5)

This will give you the probability of getting 5 or fewer successes in 10 independent Bernoulli trials with a probability of success of 0.5.