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Do you need statistics to understand your data?

Hello, and welcome back to week 2!
Today, I am posed with the question of whether we need statistics to understand our data.
Now, when it comes to this question, I am inclined to say no for one simple reason:  I had a lot of trouble with statistics in the first year of my degree, yet show me some data that has been collected, (infact, I saw data that I collected myself last year for that matter) and I could tell you what’s going on.
For example, let’s look at Milgram’s famous study of obedience.

He asked participants to play the role of ‘teacher’ and everytime their ‘student’ got a question wrong, they had to give them an electric shock of varying shock ratings (eg. slight shock, moderate shock, danger: severe shock and the slightly worrying XXX).

(For those of you who don’t know the study, there wasn’t actually anyone getting an electric shock…it was all a trick.  Sneaky these psychologists, aren’t they?)

Anyway, the results showed that of the 40 participants in the study, 26 delivered the maximum shocks while 14 stopped before reaching the highest levels. It is important to note that many of the subjects became extremely agitated, distraught and angry at the experimenter. Yet they continued to follow orders all the way to the end.*
Now, imagine you know nothing about SPSS, t-tests, ANOVAs etc.  and you’re just looking at these results.  Surely, you can tell that every single participant gave an electric shock at least once, and over 50% of them gave the maximum shock there was, just because they were told to by an authority figure.  You don’t need statistics to conclude that these participants would obey an authority figure even if it meant harming others, and even harming their own mental well-being.

*http://psychology.about.com/od/historyofpsychology/a/milgram.htm

I’m not saying that we don’t need statistics.  But do we need statistics to UNDERSTAND data that is put in front of us?  I don’t think so.  I, personally, get confused after the statistics.

I appreciate that there are data sets that may be too big or too complex to deduce what’s going on just by simply looking at the data in front of you.  And yes, for these we would need statistics to help us make sense of what we’re looking at.  But again, do we really NEED the in depth understanding of statistics, or is it just a tool to help us make quick conclusions from our data?

 

I’m probably rather bias, as I’ve never really gotten my head around statistics very well, but still, I am yet to come across some data where I couldn’t see what was going on without having to apply a lot of complicated statistics to it.  The again, maybe I just haven’t looked hard enough 😉

Next week, I’ve been given somewhat of a free pass. So I hope you all enjoy surprises.

Adios.

 

 

 

Categories: Uncategorized
  1. October 14, 2011 at 1:24 pm

    While I do see your point about being able to understand data without having to analyse it and all of that stuff, I think we gain a much deeper understanding of research if it’s been statistically analysed to prove it’s significance. If that wasn’t necessary in psychology, there would be hundreds of studies everywhere claiming to prove things that when run through SPSS, are shown to be completely untrue.
    Also, some studies don’t produce data that is as easily understandable, sometimes the SPSS stuff does actually make it a lot easier to look at and write about than just a massive list of numbers.

  2. psychrno
    October 14, 2011 at 7:48 pm

    Well, it is true that sometime we do not need statistics to understand our data. For example: Some of the theory in psychology is formed based on observation such as Freud’s psychosexsual and Pavlov ‘ classical conditioning. I also understand that statistics somehow will not be easy to study. Imagine the report of the experiments are pages with numbers and alphabets. If we did not study stats before, we wouldn’t know how to read the report or we could get confused easily by these data.

    On the other hand, it is also important that we need statistics to understand our data. For example: even though Freud’s psychosexsual and Pavlov’s classical conditioning theory is formed based on observation. However, the observation and writing report about the observation and frequency for the behavior to occur is a form of collection data in statistics.

    Furthermore, without statistics, we can’t make assumption and generalized that our results has significant effects on the populations. Besides that, we can’t exactly tell whether is there any relationship between the variables without statistics.

    significant testing – http://www.statsoft.com/textbook/nonparametric-statistics/

    This is only my opinion on statistics. =)

  3. October 14, 2011 at 7:51 pm

    I really enjoyed the fact that you went against statistics being necessary to understand data. I understand that you are suggesting that we do not necessary need statistics to understand our data even though they could be helpful with a big data set. However, Im going to suggest statistics are necessary – If we say that we understand what the data is saying (even small data sets) then we should be able to argue our opinion well and statistics allow us to do this strongly. Another area, which you could have looked into could have been types of data, but I feel you covered alot within this blog! It was an enjoyable read.

  4. October 14, 2011 at 10:56 pm

    Without analysing your data to get the statistics it would be very hard, and i’m actually betting almost impossible for you to work out if your data is significant or not, and it would be incredibly hard work too, trying to make all the numbers that SPSS spits out at you would be incredibly time consuming and extremely difficult.

  1. October 14, 2011 at 1:45 pm

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