# The difference between "only one" and "one and only one"

1. A teacher announces, "There is only one student who failed the course."

Does the teacher’s statement mean anything different from the following version?

1. "There is one and only one student who failed the course," said the teacher.
• No; the longer version has an identical meaning but allows the speaker to impart more gravitas. Commented Jun 9, 2020 at 11:18
• Two words never mean the same thing as one word. Four words never mean the same thing as two words. Never. That is true for any words. More to the point, this is a quote. You cannot change it. You have to write exactly what the teacher actually said. Commented Jun 9, 2020 at 12:03

In ordinary conversation, only one has the same meaning as one and only one. The shorter phrase is used almost every situation.

In mathematical logic, it's often desirable to make a distinction between zero or one and exactly one. In that situation one and only one is used to indicate that the count cannot be less than one or more than one.

• This answer misses the important point, which is emphasis. Commented Jun 28 at 16:00
• Wouldn't, even in formal logic, there is (i.e. the existential quantifier) rule out the possibility of the count being zero? Commented Jun 29 at 16:07

The meaning of both "only one" and "one and only one" is the same. However, "one and only one" adds emphasis to the fact that there is only one, and draws attention to it. For example, the student who is the only one who failed, might feel more ashamed if the teacher uses "one and only one", as the teacher might be perceived as purposely drawing attention to that fact, for whatever reason.

Actually, there is a difference between these two terms. In data analysis, a single time-series dataset can be used to produce a cumulative distribution curve. However, since the curve has no time component, it is common to any re-ordered dataset. There is no unique relationship between any single dataset and the resulting cumulative distribution curve.

Therefore, since a cumulative distribution can reproduce a single starting dataset, it is just one from a number of datasets with different ordered data. It is then appropriate to state that a cumulative distribution curve cannot produce one, and only one unique dataset.

• Clearly not what is being talked about here. Commented Jun 28 at 16:10