以438 226为例
binom.test(x =438, n =664, p = 0.5, alternative = "two.sided")
binom.test(x =226, n =664, p = 0.5, alternative = "two.sided")

多谢版主啊！用二项分布近似方法和修正的正态近似方法做出的结果基本相符，看来原文中可能是Frebruary 1989一栏中56.46后面少标了一个星号。
> prop.test(236,418,correct=TRUE)

        1-sample proportions test with continuity correction

data:  236 out of 418, null probability 0.5
X-squared = 6.7201, df = 1, p-value = 0.009533
alternative hypothesis: true p is not equal to 0.5
95 percent confidence interval:
0.5154876 0.6124931
sample estimates:
        p
0.5645933

> binom.test(x=236,n=418,p=0.5,alternative="two.sided")

        Exact binomial test

data:  236 and 418
number of successes = 236, number of trials = 418, p-value = 0.009451
alternative hypothesis: true probability of success is not equal to 0.5
95 percent confidence interval:
0.5155503 0.6127155
sample estimates:
probability of success
             0.5645933

您好，我最近在学习r语言中，遇到了您问题中所用的两个函数，虽然看了帮助文档，但是对这两个函数的意义还是不理解，请问这两个函数都是用来做什么的，有什么区别呢？