If you want to get the probability starting from the right tail, be sure to set lower.tail=FALSE.
By default, R will integrate the probability starting from the left tail. The q prefix, as in qf(), is how you obtain critical values from a probability distribution. This is useful if you ever want to visualize the shape of a probability distribution. You can use this to calculate likelihoods, and you can use it to plot the exact curve for a function. For an F value of 2.3, with 15 and 20 degrees of freedom, the F function is given by: Again, for the F distribution, you need to supply the degrees of freedom for the numerator and the denominator, and in this case you need to specify the value of F for which you want the F function. In other words, d gives you the height of the probability distribution. The d prefix, such as df(), is useful for finding the value of the F function, called its density, at any value of the statistic. If you generate many random numbers and plot a histogram, you can see the approximate shape of that F distribution. To generate n=50 random numbers, you would type For the F distribution, you need the degrees of freedom for the numerator ( df1) and the denominator ( df2). Most distributions require one or more parameters to define the shape of the distribution. When you want to generate random numbers, use the r prefix, as in rf() for the F distribution. Let's look at each of these functions, but we'll use the F distribution. If you combine these with the name of the distribution - rnorm(), dnorm(), qnorm(), and pnorm(), for example - you can generate random numbers, find the value of the function at a specific point, produce a critical value, and calculate a p-value. R comes with a rich set of probability distributions, and four consistent ways of accessing them: r, d, q, and p.
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