请把下面一段英文翻译成汉语，要求通俗易懂（摘自数据结构）
The data types in the RAM model are integer and floating point. Although we typically do not concern ourselves with precision in this book, in some applications precision is crucial. We also assume a limit on the size of each word of data. For example, when working with inputs of size n, we typically assume that integers are represented by c lg n bits for some constant c ≥ 1. We require c ≥ 1 so that each word can hold the value of n, enabling us to index the individual input elements, and we restrict c to be a constant so that the word size does not grow arbitrarily. (If the word size could grow arbitrarily, we could store huge amounts of data in one word and operate on it all in constant time-clearly an unrealistic scenario.)
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The data types in the RAM model are integer and floating point.
整形和单精度浮点类型是RAM模型中的数据类型。
Although we typically do not concern ourselves with precision in this book, in some applications precision is crucial.
尽管，我们不会特别注意本书中的精度类型，但是在某些应用中，精度还是至关紧要的。
We also assume a limit on the size of each word of data.
我们通常会假定数据中每一个“字”（个人认为，word 在这里表示意思需要推敲，目前暂且认为是数据中的一个“数字”的意思）所占空间大小的限度。
For example, when working with inputs of size n, we typically assume that integers are represented by c lg n bits for some constant c ≥ 1.
例如，当遇到输入大小为长度n时，我们通常假定整形用clgn位来表现（数学好的同志来帮帮忙，这段lg函数，偶看不懂和字的长度有啥关系），c为不小于1的常数。
We require c ≥ 1 so that each word can hold the value of n, enabling us to index the individual input elements, and we restrict c to be a constant so that the word size does not grow arbitrarily.
我们需要c不小于1，这样每一个“字”能够占据n个长度，使我们可以给独立输入的元素建立索引，并且我们约定c是一个常量，使这“字”的长度不会任意增长。
(If the word size could grow arbitrarily, we could store huge amounts of data in one word and operate on it all in constant time-clearly an unrealistic scenario.)
如果“字”的长度会任意增长，那么我们可以存储大量的数据在一个字当中，并且在假定不切实际的时间内操作这个字。
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见《算法导论》 p.22 第二段