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There's an example in my textbook about cancellation error that I'm not totally getting. It says that with a $5$ digit decimal arithmetic, $100001$ cannot be represented.

I think that's because when you try to represent it you get $1*10^5$, which is $100000$. However it goes on to say that when $100001$ is represented in this floating point system (when it's either chopped or rounded) it comes to $100000$.

If what I said above is correct, does $100001$ go to $100000$ because of the fact that it can only be represented like $1*10^5$?

If I'm completely off the mark, clarification would be great.

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3 Answers 3

up vote 2 down vote accepted

Yes, you only have five decimal digits available. $100001=1.00001*10^5$ but I have six digits in the mantissa. Clearly it is closer to go to $1.0000$ than to $1.0001$, so that is what we will do. So the numbers around here that can be represented are $99998, 99999, 100000, 100010, 100020,$ etc.

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Also on another note would the largest number be 9.9999 * 10^(whatever exp was max)? –  wzsun Feb 13 '13 at 1:23
@wzsun: that is correct. –  Ross Millikan Feb 13 '13 at 1:29

I think the point is about the precision of the number that can be stored, not so much the exponent. In other words you cannot store $1.00001*10^5$ because it cannot store five decimal places of precision. Equally it would not be able to store $1.00001*10^{15}$ or $1.00001*10^{-5}$.

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That is correct. You have what is called type overflow. Want to be amused? If you have a C compiler run this program

int main(void)
    int x = 1;
    while (x > 0)
        x = x + 1;
    printf("x = %d\n", x);

It's educational. This is in integer-world so it's simpler than floating point numbers, but these have an analogous problem: loss of precision. I recommend Forman Acton's Real Computing Made Real for a discussion of this issue.

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I don't recall my C very well, but why wouldn't the while fail the first trip through? It also seems like if your compiler defaults to 32 bit ints you might have a bit of a wait. Should it print x=-1? –  Ross Millikan Feb 13 '13 at 1:28
Note correction. Sorry about the error. –  ncmathsadist Feb 13 '13 at 1:38
Integer overflow is a very different situation than floating-point loss of precision. –  Nate Eldredge Feb 13 '13 at 1:47
It is a similar problem. The bits run off the end and you get in trouble. –  ncmathsadist Feb 13 '13 at 2:03
Go look at how IEEE 754 works. –  ncmathsadist Feb 13 '13 at 2:04

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