How reliable are certain scientific statistics?

In summary: For example, if you took a sample of 100 women and found that only 1 of them conceived after 44 years old, that would be statistically significant, right? Wrong. The real significance would be if you took a larger sample and found that out of 1000 women who tried to conceive after 44, 800 of them conceived. Statistically speaking, this would be a much more meaningful result.In summary, statistics in science can be unreliable due to the fact that they are based off of a small sample size, and that the chances of a particular phenomenon occurring are not as low as the statistic would make them seem.
  • #1
Solid Snake
26
0
First, sorry if this is in the wrong section. This could span many subjects.

I was pondering on how reliable statistics in science are. My mother's best friend just had a baby naturally at 45 years old. I also know 3 other women who have had babies naturally after 40 (specifically 2 of them at 44, and the other at 45). Yet when I read up on the statistics about how possible it is to have babies after 40 (especially at the mid-40s) it would seem almost impossible that I know 3 women who have naturally had babies (especially since they're all over 44). This makes me think that such statistics are unreliable. This has to be true in medicine and biology since it is difficult to know things about the body with such precision. I can imagine in other parts of science, the same applies, though in physics it's probably less so.

So how reliable are statistics in science? In biology?? With the human body?? In geology? Cosmology? etc

EDIT: Also I'd add about those stats about women being able to naturally make babies in their early-to-mid 40s, there are so many ranges that differ. For example I read one that stated how it's only a 1% chance at 44, when other said its a 30%, and it ranges from the fathers age (the younger the father the better). Yet other statistics say the fathers age is irrelevant. This makes me believe that there exists some faults in certain subjects in scientific statistics.
 
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  • #2
There are several statistics that you are intermingling erroneously.

One is the statistics of women over 40 who have given birth.
Another is the possibility of a woman over 40 conceiving, due to the physical changes in the body brought about by age.
Another is the chance that a particular individual knows a woman over 40 who has given birth.

The fault lies not in the statistics, but the interpretation.
Sometimes that is difficult to do.
 
  • #3
Your problem is that you only are looking at a very small sample. Let's suppose that the data shows that only 1 in 100,000 women 40 years old and older will ever be able to conceive a child (I'm completely making this up to demonstrate the phenomenon) and there are ten million 40+ women trying to conceive. That means that 100 of them statistically will. If you only look at those 100 then of course it's going to seem like the original data is wrong, but taken as a whole it makes sense.

Furthermore the chances of conceiving after 40 really aren't as low as you make out to be. According to http://www.extendfertility.com/downloads/documents/NEJM_AdvancedMaternalAge_HowOldIsTooOld.pdf pregnancy rates in women less than 30 years old are 400 in 1000, dropping to 100 in 1000 for over 45s. The miscarriage rate for the latter group is much higher at 90% but that still leaves a relatively large (10 in 1000) number that successfully give birth. That doesn't take into account complications like increasing risk of Down's syndrome (see this paper for more information on the risk of birth defects) but you get the idea.
 
  • #4
The moral of the story: don't expect statistics to provide protection against pregnancy when more effective means are available.
 
  • #5
Simply, statistics are more reliable on a subject that is more uniform or presumed to be: subjects like physics and chemistry. When you move into the realm of medical science, the genetic diversity and differences in populations really stress that you have an adequately large, possibly unfeasible/ethical sample sizes. Statistics become even more hairy in the social/political sciences.

Simply because you know three women in the mid forties who have had children doesn't disprove the statistic. The journal that is pulled out of is the journal Fertility and Sterility and their sample size is larger, which trumps your anecdotal experience. The only real conclusion to draw from the statistic is that women over the age of 40 rapidly lose fertility with each passing year.
 
  • #6
And then there are statistically significant results that are biologically meaningless...

There have been many, many papers over the years written on this subject and our over reliance on 'statistical significance' within biomedical research. A statistically significant phenomena might not mean a damn thing.
 

1. How do scientists determine the reliability of their statistical findings?

Scientists use a variety of methods to determine the reliability of their statistical findings. This can include conducting multiple experiments, using control groups, and performing statistical analyses to determine the likelihood of their results occurring by chance.

2. Are scientific statistics always accurate?

No, scientific statistics are not always accurate. They are estimates based on data and can be influenced by a variety of factors such as sample size, measurement error, and bias. However, scientists strive to minimize these potential sources of error to improve the accuracy of their statistics.

3. Can scientific statistics be manipulated to support a particular agenda?

Yes, scientific statistics can be manipulated to support a particular agenda. This is why it is important for scientists to follow ethical guidelines and transparently report their methods and results. Peer review and replication of studies can also help identify any potential manipulation of statistical data.

4. How can the general public determine the reliability of scientific statistics?

The general public can determine the reliability of scientific statistics by evaluating the source of the information, checking for any potential bias or conflicts of interest, and looking for supporting evidence from other studies. It is important to critically evaluate and understand the methods and limitations of statistical findings.

5. What happens if a study's statistical findings are found to be unreliable?

If a study's statistical findings are found to be unreliable, it can call into question the validity of the entire study. This can lead to further investigation, replication of the study, or retraction of the findings. In order to maintain scientific integrity, scientists must be transparent about their methods and open to scrutiny and correction if necessary.

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