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May 14, 2012 / chimk

What’s Behind Statistics?

It is easier for accountants to agree than scientist, simply because science doesn’t have a one fit answers for a problem. The result depend on what was found to be true at that particular time, based on facts at that particular point in time. But what is it that science communicator has to do to have a better understanding of the research outcomes?

You don’t need to master nitty-gritties of statistics in order to understand and communicate scientific findings, however probing of the findings need to done to separate the truth from trash. Lewis Cope in his article “Understanding and using statistics”  is trying to give us the ways which will help in digging for more information behind the statics.

He starts by explaining more on “Probability, Power and large numbers” principle which takes care of results by chance. These results can be avoided simply by having a large sample size. The other thing to be considered here is the likelihood of a certain result to be obtained. He gave an example of cases  of ”lung cancer in smokers” , this is an obvious things, we all know that smoking causes lung cancer and it not strange to find a  smoker diagnosed with this type of cancer.

Check biasness of the conclusions of the study or explanations of the results. Failure to consider other researchers findings or explanations on similar topic shows unprofessionalism. In doing a research it is either a certain point of view is being verified to be true or not, so it is actually a revolving story from somewhere else, so the new discoveries has to be compared to other findings done in the same study area.

Another principle is that of trusting some studies based on impact or indication the findings will have.  As stated by Lewis Cope, epidemiological studies tend to study mites to find the effectiveness or dangers of some medicines, vaccines, or chemicals to human beings, so despite the sample being involved in these kinds of studies is small, the impact is great.

Peer review is another thing that also strengthens statistical findings, in every field of study there are professionals who can either agree or disagree with a research finding, find out if the researcher has considered other explanations from his peers and if there are any disagreements check the reasoning the differences.

Statistical distribution of the results needs to be considered as well, “how many samples are above or below average. This will give a good clue on the general outcome of the research.

Assess if correct sampling technique was used. All the above mentioned “principles” will hold if the sampling technique used was correct. Some researchers can deliberately choose a certain way of sampling just to get the result they want which cannot be a true reflection of realities.  As indicated earlier, that the larger the sample the better the result, but if that large sample was not randomly selected, the result will not a true representation .For instance using online survey to assess a general acceptance of something by a nation. Online survey will automatically screen out a population that does not have access to internet. Random sampling is always the best way of achieving a better result.

This article gave an insight of what to look for in research statistics to have a clear idea before communicating to the general public, do you agree?

Reference

Cope, L.  Understanding and using statistics. In Blum D, Knudson M & Henig RM (Eds), A field guide for science writers (pp 18-25).

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8 Comments

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  1. muza2009 / May 16 2012 2:31 am

    Lewis Cope’s article is a great reference for science writers on understanding statistics and Elizabeth you have done well in summarizing some key points bar a few typos. I think the blog could have been structured better by stating near the beginning the points you will cover or summarizing them at the end e.g. When assessing the statistics presented in scientific research, science writers can look at statistical distribution, bias, dis-confirming evidence, sampling and the sample size of the research.

    I was not clear what you meant by statistical distribution.

    I am curious as to whether you found the article useful? Did you learn anything new or think it was missing something?

  2. elenav90 / May 17 2012 4:56 am

    I must admit, not the most riviting topic to write about, and your title didn’t motivate me to your article at all. Yet, I thought the other post would get more comments so I tried to engage with your piece.

    Unfortunately, your very first sentence was poor in grammar and meaning. But I soon notice that your writing does not improve throughout the post… It would have been a great idea to give the text to someone else to proof-read, and doing something about a few of the many flow and grammatical flaws.

    Also, sorry but adding a “do you agree?” at the end of the post doesn’t translate into reader engagement. It seems indeed that you’re providing a summary of the Cope’s article but without really appreciating it yourself, you didn’t ‘add’ anything to it, I agree with Muza in regards to this.

    The actual topic was, of course, very important. Statistics directly influence the interpretation of results. Importantly, I believe we normally just give statistics unquestionable authority because we trust their format, their presentation, we accept that they render valid the argument they support. Possibly, we actually give them the authority we would allow to its source, so perhaps a scientist presenting some statistics might make the numbers sound more reliable and valuable than they would if presented in a magazine. This is because most of us have never truly considered the guidelines elucidated by Cope!

    Thanks for teaching us something new.

    • elenav90 / May 17 2012 5:28 am

      Sorry, I forgot to point out that you may have forgotten to include your image…

  3. thiarayoanita69 / May 17 2012 3:41 pm

    In my opinion, statistic is simply powerful. It depicts the significance of an issue. For instance, in my previous unit, we were discussing about the seven most prevalent diseases in Australia. One way to decide their “ranking” was from the number of population who suffered that particular disease.

    In response to the actual question, “What advice would you give to a science writer regarding using statistics in a news article?”, I think that statistic should be incorporated in the introduction of a writing to convey the effect size of the condition. Moreover, as Cope wrote, statistic in terms of dollar figure may be necessary to include after the proposed treatment as well. I feel people are interested to know how much changes would this treatment bring.

    Coming back to your writing, I slightly disagree to what you said about “Failure to consider other researchers findings or explanations on similar topic shows unprofessionalism.”.. I personally think what Cope wanted to emphasize is that biasness leads to doubt about validity of the finding. I also would like to add to what you have said earlier – “Probability, Power and large numbers principle which takes care of results by chance. These results can be avoided simply by having a large sample size.” In this, Cope also mentioned another important feature of statistic – that although large sample size may help to show significance of a finding, but this does not always justify the finding to be true. It just aids in reliability of the study. One more thing that I feel the urge to comment on, is about your statement regarding random sampling as the “best way”. How about a case study? because I do not think that participants in case study are randomly selected..

    Overall, you have done a quite good job in summarizing some of the key features that Cope proposed. However, as Muza and @elenav90 have said previously, I found it pretty hard to follow your line of thoughts. I guess if you did some rewording, a couple of grammatical changes, and restructure the style of the blog, it would really help in improving the clarity of your writing (:

  4. suyinnn / May 18 2012 5:42 am

    Hello! I agree that statistics is a key aspect in life, as many things that revolve around us can be calculated through the use of probabilities. Good job in summarising the definitions with examples.

    I agree with muza that you could have structured this post better by including an introduction and a conclusion that highlighted the main points in your article.

    I’m sorry to say but I did not find your article interesting, as there was no pictures attached and the title was not eye catching. There were a few grammatical mistakes, and I guess you have avoided that by asking your friends for help to review your article beforehand. You mentioned about ‘peer review’ in your article, maybe next time you could try to put that into practice? :p

    Nonetheless, a good effort. (:

    • chimk / May 20 2012 9:14 am

      Thanks for your comments, and inhave taken note of your advice.

  5. lachlanpetersen / May 31 2012 8:54 am

    I agree with Muza also, your post was a nice summary of the article but it would have been good to discuss something other than just what’s in the paper. I understand you didn’t have much to work with though, I can’t really think of anything that could be said unless you really knew your statistics and could critique the article, but then no-one would understand what you were talking about.
    I think you did well, considering.

  6. tobiasgrey / Jun 8 2012 12:37 pm

    I like this post, and the article. Stats is an important part of understanding science, and being a scientist. You give a good summary of the article and some nice (not 100% clear, but everything that needed to be mentioned was mentioned). Kudos!
    Unfortunately, the discussion topic isn’t really up to par with the rest – a conversation about stats more specifically may have been a better direction. But then, I’m a stats nerd, so I’m biased.
    Congrats on a good article.

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