STATISTICS AND TYPES OF
BIOLOGICAL DATA. (part one)
(Based on Jerrol H. Zar
Fourth edition Biostatistical Analysis
book)
Hello again everyone, so long after the last
post uploaded, uh?, so, this time I want to post about a new topic that I think involves
whoever that reads this kind of blog.
Well, just
like the name of the entry says, let’s start talking about the word statistics, which is derived from the Latin
voice for state , this word is
related principally to demographic information
(like census data) and tax collecting. For the most of us, when we hear
the word statistics we associated it with
the term data, thinking in a
quantitative approach, like, how many students from each geographic location enrolled
to a college, statistics related to sports, labor statistics (numbers of
workers unemployed, numbers of employed in various occupations) and so on and
on, but in fact (sorry to disappoint) this is the WRONG approach, at least in order to understand all the data (biological
data in this case) and its behavior we have to change this paradigm. After this point (and forward) let’s think that
statistic means or refers to: the analysis and interpretation of data with
a view toward objective evaluation of reliability of the conclusions based on
the data (trust me!! It’s not my quote, is a J.H. Zar advice ;) ).
And what does the biostatistics word means?? What else but statistic related to biological problems, sounds simplistic (maybe even dummy) but that’s the way it is, so we can call it with Karl Pearson conceived term biometry, but today this could sound pretentious, in my personal opinion, a pretentious dude that speaks about statistic is just a bluffing liar (but I’m just a kid :P). So despites this, the biometry word talks us about of a biological measurement that in the end is its literal meaning.
At this point maybe you’re wondering, when we’ll
start to calculate stuffs and predict the future and impress that girl with our
sexy biological statistics assumptions?? (speaking about bluffers), well,
before data can be analyzed, they must be collected, and another important fact
is BEFORE DATA CAN BE ANALYZED, THEY MUST BE COLLECTED, was I clear??. So this
isn’t the moment to talk about design of the experiment, but I have to tell that
before collecting data and before the experiment begins we have to know what the heck
we try to answer.
Once we have the data we apply something called descriptive statistics:
this consist in getting the data arrive at their orderly and informative
presentation. That way if we have a bunch a data well organized we can do some generalized conclusions, for example, if I have a table with the glucose serum
levels of a certain population ordered by gender side by side, maybe we might wish
to conclude that the females are more sweet than males (I’m joking), what I mean
is, we might wish to conclude that the average glucose levels in males are higher
than the females levels. We have to get in count that this conclusions are inferring
characteristics of the whole from characteristics of its parts, this is the inferential statistics, we’ll talk later
of this last “kind of statistic”.
Well this is the end of the PART ONE of this topic, in PART TWO we're going to talk about the types of biological data, so I'm going to try to give some examples by my own, but remember that this topic series are based in the book that is in the references at the bottom.
See you later,
please comment and suggest topics.
What do you
understand for the word STATISTIC??
What is the first thing that comes to your mind when you hear the word statistic, … and when you hear Biostatistics??
:)
Reference:
J.H. ZAR,
BIOESTATISTICAL ANALYSIS, 4th Ed. Prentice Hall, New Jersey, EUA,
1999, 663 pp.
