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Why is the area to the left of the mean different in normal distributions comparatively to exponential distributions?

I understand that in normal distributions area is allocated symmetrically on either side of the mean, in which it is defined by its mean and standard deviation. Conversely, do I understand correctly that the area in exponential distributions is varied? How best would area be described in this model? Is it different because the mean and standard deviation have the same value in exponential distributions?

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    $\begingroup$ Have you seen the exponential and normal densities? Are you able to clearly articulate what's unclear about why their incomplete integrals differ? $\endgroup$
    – Glen_b
    Feb 14, 2015 at 10:07
  • $\begingroup$ Can there maybe be a way of moderator determining/voting/marking or whatever threads as not being worthy of ever being bumped by community? This is an example thread which is not worthy in my opinion. $\endgroup$
    – Mark L. Stone
    Sep 30, 2015 at 10:15
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    $\begingroup$ @Mark Yes, there is: upvote an answer. It shouldn't get bumped after that. (If there isn't one, provide one and someone else might do it) $\endgroup$
    – Glen_b
    Nov 8, 2015 at 6:49

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The exponential and the normal distribution are sufficiently different that it is hard to see what the confusion might be here. Here are the pdfs (copied from Wikipedia); exponential:

enter image description here

normal:

enter image description here

I wonder if you are confusing the exponential distribution with the double exponential distribution, which has a similar sounding name, but is symmetrical and is (quoting Wikipedia)

...reminiscent of the normal distribution; however, whereas the normal distribution is expressed in terms of the squared difference from the mean μ, the Laplace density is expressed in terms of the absolute difference from the mean.

enter image description here

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