Sunday 14 September 2008

Tomatoes with no light

We are growing tomatoes for the first time. It is very interesting looking after new living beings at home. Our salads are also a bit more interesting now. For some reason I started wondering what would happen if tomatoes get no light. Are they red because of light? What about the leaves? Checking the local library or wikipedia you can get fast answers. I am not an expert, but after all I am not completely green in this subject, I know the basic things everybody can remember from school: chlorophyll, chloroplasts and so on.

But there is something that the local library, wikipedia and my teenager memories cannot fulfill: they cannot give me my own answer.

And that's why I made this experiment.

As with every experiment, I need an...

Idea to test: Plants are green because of sunlight, so if they get no light they will not be green, as they cannot photosynthesise. That's what we expect. And what about tomatoes? Somebody told me they are red colour because of carotenoids, the organic pigments produced by plants along with chlorophyll. Carotenoids, especially lycopene, absorb blue light and reflect red light.

So, the idea is: if a leaf cannot photosynthesise, it will be any colour but green, and if the tomato cannot photosynthesise, it will be any colour but red or green. Maybe yellow, maybe brown, but not the usual colour. Here is the specific idea I want to test:

If I wrap a tomato leaf up in aluminium foil, after some days it will start losing it natural green colour, and if I do the same to a tomato it will also lose its red or green colour.

The material: Aluminium kitchen foil, bought in the local supermarket, and a tomato plant.

The set-up and measures: Well, I have not a "green-meter", so to compare the differences I just took photos from time to time. The experiment lasted 39 days.

3rd August

The experiment starts!

Unfortunately I didn't take a photo of the tomato leaf before wrapping it up, so you will have to believe me when I say that it was pretty the same than the other non-wrapped leaves you can see in this photo:

For the tomato, I chose one from a branch with four tomatoes, so I could compare better the differences between the selected tomato and its "brothers". Here is how this branch looked like in a previous photo I took on 28th July:

Here is a closer view:

And here is the same branch with the wrapped tomato on 3rd August:

8th August

This is how the leaf looked like some days later:

Its end was a bit damp (which probably was due to the fact that it had been in a closed space), but it looked as green as it was the first day.

Unfortunately I didn't take a photo of the unwrapped tomato, but there were not many changes as well: the four tomatoes were very green, and probably not very tasty.

11th August

The leaf looked as green as the other leaves, but touching it I could feel it was weaker, softer than the rest.

The tomato was a bit smaller than the other three (which could be casual), but no sensible changes were observed:

30th August

Here is how the leaf looked like almost four weeks later (obviously, the only moment when I removed the aluminium foil was while taking the photos):

there are no major changes in colour, but the wrapping is centainly affecting the leaf's health. Now the end of the leaf looks like burned, and perhaps a bit more yellowish.

However, the tomato looks perfect (it's the left one in this photo):

Note that one of the four brothers (the one at the back which can barely be seen) is getting redder and redder!

11th September

Last day. The "leaf disease" is in an advanced state and the "patient" will probably not last very long:

The colour is still green, maybe a bit more yellowish near the edge at the end.

Two of the four tomatoes were eaten in a great salad, but we left one brother to compare with the selected tomato:

They are both fairly red and start looking very tasty, but wait... what's at the bottom of our friend? Maybe we can see better from below:

oh, it looked so healthy, but actually was starting to rot away! More or less the same that happened to the leaf. But the colour is exactly the same as its brother's colour.

Conclusion: During these 39 days I have not seen too many changes in colour, which has been surprising. However, the aluminium foil has obviously affected both the leaf and the tomato, as they started to rot away. I can think of three reasons for this:

  • lack of light weakened them, making them more vulnerable,
  • closed space kept them wet, which contributed to the rotting process,
  • the tight contact with aluminium, which is not quite natural for a tomato plant, could have triggered the rotting process.

Anyhow, colour didn't change discontinuously at the edge of the aluminium foil, as I thought. Why? Are chloroplasts distributed evenly through all the plant, regardless of the place where they photosynthesise? Maybe it can be interesting making another experiment covering the whole plant, to check how different is its colour from the colour of another plant with good sunlight. But for the moment... let's eat a salad!

Sunday 24 August 2008

Games about the Olympic Games

The 2008 Olympic Games are over, and as expected, China has been the country with most gold medals (but curiously, not the country with most medals!). It might be easy to think that statistically a country with over 1.3 billion people has to have at least some good athlets. There seems to be a not surprising correlation between population and results in the Olympics.

The idea: Good, we have the following belief

There is a strong correlation between the population of a country and the results in the Olympic Games

is that something real, or am I fooling myself?

The material: To do this, I didn't need too many things, as I just took data from wikipedia about the medal count and the population.

The set-up: I calculated the following score for each country:

  • gold medal = 1
  • silver medal = 0.5
  • bronze medal = 0.25

and then I got the list you can find at the end of this post. If we order it by total score (I preferred to order it by score/million people, which is more interesting), the list is not quite different from the original medal count, which is ordered by gold medals, then by silver medals, and then by bronze medals. China is still the number one, but United States is a bit nearer.

Ordered by score/million people, we see that... Jamaica, with a score of almost 3 is leading! (It pays having good short distance runers) Then we have the Bahamas, Iceland... The first big country is Australia (which has been amazing about every sport that is related with water).

I have made the following graph showing the relation between my score and the population:

Clicking on the graph you will see the original size, with the name of each country for each cross. But anyway, you will not see too much, as most of the countries are piled up in one corner. Maybe you can see better in logarithmic scale:

I have added the linear fit calculated using Origin. If we have to trust in the Origin, the correlation coeficient is 0.398.

This means that there is a weak, direct correlation between results and population. It is what I expected... but not as much as I expected (personally I thought it would have been a correlation around 0.8).

Why is the correlation so weak? I think one reason could be the fact that in most cases the medals are just one or two, which is not enough to get good statistical results, as fluctuations can change a lot the score, so we have "good" information just about countries that have at least ~10 medals

The other reason could be the fact that population is not the only important factor here. For example, the economy of a country is also important.

It's late enough now, so I will not make a graph showing the score versus the GDP, but if somebody does, I am interested in seeing the result.But just let's make one more graph. I choose only the countries that have got at least ten medals (not because they are more important than the other, but because the statistics are more accurate), and here is the result:

Interesting, isn't it? The bigger the country, the smaller the score. And here the correlation is a rather strong: -0.807. It seems that a single athlete has more chances to win a medal if he is from a smaller country (probably because there is less internal competition to qualify for the Olympics). That makes me think of the half-Togolese half-French kayaker Benjamin Boukpeti, who preferred to defend the Togolese flag instead of the French one, because it was much more difficult to qualify as part of the French team. After all, he got the first medal for Togo!

Conclusion: So it comes out that

1) big countries have more chances to get medals, because they have more people to select and train, but the correlation is much weaker than expected.
2) for the individual, being in a big country can be counterproductive, probably because there is more internal competition to qualify for the Olympics.


OK, here is the promised table (as I am European, I wanted to see what are the results of my "bigger country", so I have added the data for the European Union below).

For space reasons, the medals are shown in format gold/silver/bronze=total. Population is in millions. And remember, score = #gold + #silver/2 + #bronze/4. (I have made also a map that you can see on Wikipedia).

Country Pop. Medals Score Score/pop.
1. Jamaica 2.714 6/3/2=11 8 2.948
2. Bahamas 0.331 0/1/1=2 0.75 2.266
3. Iceland 0.316 0/1/0=1 0.5 1.582
4. Bahrain 0.76 1/0/0=1 1 1.316
5. Norway 4.778 3/5/2=10 6 1.256
6. Slovenia 2.029 1/2/2=5 2.5 1.232
7. Australia 21.394 14/15/17=46 25.75 1.204
8. Mongolia 2.629 2/2/0=4 3 1.141
9. Estonia 1.341 1/1/0=2 1.5 1.119
10. New Zealand 4.274 3/1/5=9 4.75 1.111
11. Belarus 9.69 4/5/10=19 9 0.929
12. Cuba 11.268 2/11/11=24 10.25 0.91
13. Georgia 4.395 3/0/3=6 3.75 0.853
14. Slovakia 5.402 3/2/1=6 4.25 0.787
15. Latvia 2.268 1/1/1=3 1.75 0.772
16. Trinidad and Tobago 1.333 0/2/0=2 1 0.75
17. Denmark 5.489 2/2/3=7 3.75 0.683
18. Netherlands 16.445 7/5/4=16 10.5 0.638
19. Hungary 10.043 3/5/2=10 6 0.597
20. Lithuania 3.361 0/2/3=5 1.75 0.521
21. Armenia 3.002 0/0/6=6 1.5 0.5
22. Great Britain 60.587 19/13/15=47 29.25 0.483
23. Czech Republic 10.403 3/3/0=6 4.5 0.433
24. South Korea 48.224 13/10/8=31 20 0.415
25. Switzerland 7.637 2/0/4=6 3 0.393
26. Croatia 4.555 0/2/3=5 1.75 0.384
27. Finland 5.317 1/1/2=4 2 0.376
28. Kazakhstan 15.422 2/4/7=13 5.75 0.373
29. Azerbaijan 8.467 1/2/4=7 3 0.354
-. (European Union) 498.248 87/101/92=280 160.5 0.322
30. Germany 82.218 16/10/15=41 24.75 0.301
31. Panama 3.343 1/0/0=1 1 0.299
32. France 64.473 7/16/17=40 19.25 0.299
33. Bulgaria 7.64 1/1/3=5 2.25 0.295
34. Ukraine 46.059 7/5/15=27 13.25 0.288
35. Russia 141.889 23/21/28=72 40.5 0.285
36. Canada 33.347 3/9/6=18 9 0.27
37. Italy 59.619 8/10/10=28 15.5 0.26
38. Romania 21.438 4/1/3=8 5.25 0.245
39. Sweden 9.215 0/4/1=5 2.25 0.244
40. Spain 46.063 5/10/3=18 10.75 0.233
41. Ireland 4.339 0/1/2=3 1 0.23
42. Kenya 37.538 5/5/4=14 8.5 0.226
43. United States 304.875 36/38/36=110 64 0.21
44. Mauritius 1.262 0/0/1=1 0.25 0.198
45. Zimbabwe 13.349 1/3/0=4 2.5 0.187
46. Poland 38.116 3/6/1=10 6.25 0.164
47. Dominican Republic 9.76 1/1/0=2 1.5 0.154
48. Belgium 10.585 1/1/0=2 1.5 0.142
49. Portugal 10.623 1/1/0=2 1.5 0.141
50. Kyrgyzstan 5.317 0/1/1=2 0.75 0.141
51. North Korea 23.79 2/1/3=6 3.25 0.137
52. Greece 11.147 0/2/2=4 1.5 0.135
53. Austria 8.341 0/1/2=3 1 0.12
54. Japan 127.69 9/6/10=25 14.5 0.114
55. Tajikistan 6.736 0/1/1=2 0.75 0.111
56. Singapore 4.589 0/1/0=1 0.5 0.109
57. Serbia 9.858 0/1/2=3 1 0.101
58. Uzbekistan 27.372 1/2/3=6 2.75 0.1
59. Tunisia 10.327 1/0/0=1 1 0.097
60. Argentina 40.302 2/0/4=6 3 0.074
61. Moldova 3.794 0/0/1=1 0.25 0.066
62. Ethiopia 79.221 4/1/2=7 5 0.063
63. Cameroon 18.549 1/0/0=1 1 0.054
64. Turkey 70.586 1/4/3=8 3.75 0.053
65. China 1325.544 51/21/28=100 68.5 0.052
66. Thailand 63.038 2/2/0=4 3 0.048
67. Chinese Taipei 22.99 0/0/4=4 1 0.043
68. Togo 6.585 0/0/1=1 0.25 0.038
69. Ecuador 13.341 0/1/0=1 0.5 0.037
70. Brazil 187.474 3/4/8=15 7 0.037
71. Israel 7.303 0/0/1=1 0.25 0.034
72. Chile 16.763 0/1/0=1 0.5 0.03
73. Morocco 31.224 0/1/1=2 0.75 0.024
74. Algeria 33.858 0/1/1=2 0.75 0.022
75. Mexico 106.683 2/0/1=3 2.25 0.021
76. Malaysia 27.17 0/1/0=1 0.5 0.018
77. Iran 70.496 1/0/1=2 1.25 0.018
78. Colombia 44.513 0/1/1=2 0.75 0.017
79. Sudan 38.56 0/1/0=1 0.5 0.013
80. South Africa 47.851 0/1/0=1 0.5 0.01
81. Indonesia 231.627 1/1/3=5 2.25 0.01
82. Afghanistan 27.145 0/0/1=1 0.25 0.009
83. Venezuela 27.954 0/0/1=1 0.25 0.009
84. Nigeria 148.093 0/1/3=4 1.25 0.008
85. Vietnam 87.375 0/1/0=1 0.5 0.006
86. Egypt 75.201 0/0/1=1 0.25 0.003
87. India 1136.75 1/0/2=3 1.5 0.001

PS: I have seen that a wikipedian has made some interesting maps showing:

Sunday 10 August 2008

Between twelve and five

Two months ago or so I spent some hours at the Hodges Figgis (a bookshop I love, which is on Dawson Street, here in Dublin). I love to go to the second floor and leaf through the books of the scientific section. It is the closest thing to the Casa del Libro in Madrid. There I found a book, The Maths Gene, by Keith Devlin. On page 19 (of that edition) there is the following test:

You have to answer as quickly as you can:
1 - 1 = ?
4 - 1 = ?
8 - 7 = ?
15 - 12 = ?

And now, quickly, choose a number between 12 and 5!

Supposedly you have chosen seven (the full story can be found also here). I can't remember now what did I choose, but it wasn't seven. So the first thing I thought was "hm, this is not quite serious". But of course, you cannot say something like that and believe it straight away. An experiment is needed... hooray!

The idea: Let's test this idea:

When you ask somebody to make subtractions and then you ask him/her for a number between two numbers, he/she unconsciously keeps subtracting.

The "material": 36 people took part in my experiment (all of them friends, relatives and colleagues).

The set-up: To do this experiment, I spent one week asking people I know for subtractions and numbers. Obviously, I didn't tell them anything beforehand, or otherwise they would have been conditioned to give an "interesting" answer. I always asked them in the office corridors, at the end of a phone call and so. This way, they didn't have a lot of time to think.

Firstly I considered two groups, twelve people each:

Group A: I made the experiment exactly like in Keith Devlin's book, with the same subtractions to do.

Group B: I told them "give me a number between 12 and 5" (not asking them for any subtractions).

The measures: I made some mistakes, like asking for a number between 7 and 12, but obviously I excluded these cases.

Here are the results for the group A:

answer 5 --> 0 people.
answer 6 --> 2 people.
answer 7 --> 7 people.
answer 8 --> 1 people.
answer 9 --> 1 people.
answer 10 --> 0 people.
answer 11 --> 0 people.
answer 12 --> 1 people.

And here are the results for the group B:

answer 5 --> 1 people.
answer 6 --> 1 people.
answer 7 --> 6 people.
answer 8 --> 2 people.
answer 9 --> 2 people.
answer 10 --> 0 people.
answer 11 --> 0 people.
answer 12 --> 0 people.

May be it is clearer with a couple of graphs:

Group A:

OK, maybe it is not a 90% of people, but slightly more than one half picked up seven. This was surprising for me.

Group B:

I would say both graphs are very similar! With subtractions seven people answered seven, and without subtractions it was six people. Yes, if you say we cannot expect great statistics out of twelve people you are right. But anyway, this is indicative that asking for subtractions is not the key point here.

What is the real reason? I would say lots of people like number seven, the "lucky number", and would have answered that even if I had asked for a number between 1 and 100. There is a group of "fans of number seven", but how large is this group?

What if the main point is the order we ask for the numbers? I kept asking all the time for a number "between twelve and five", but it would be more natural asking for a number "between five and twelve". So, I extended the experiment and considered a third group:

Group C: I told them "give me a number between 5 and 12" (in this more natural order, not asking for any subtractions).

This sub-experiment was to check the following sub-idea:

If you ask for a number "between twelve and five" most of the times you get seven; if you ask for a number "between five and twelve" you keep getting seven.

And this was the result:

answer 5 --> 1 people.
answer 6 --> 1 people.
answer 7 --> 3 people.
answer 8 --> 2 people.
answer 9 --> 4 people.
answer 10 --> 1 people.
answer 11 --> 0 people.
answer 12 --> 0 people.

Or, more graphically,

Group C:

Funny, isn't it? Seven is not any more the preferred number! It would be interesting to check this with a larger group of people, to make sure that fluctuations are not fooling us.

Conclusion: Recognising that groups of 12 people to choose between eight numbers is not a great deal, we can provisionally say that

  • asking for subtractions before making the "important" question is not the key point for the number the people has to pick up when asked for a number between twelve and five (though there can be some influence smaller that the error of this experiment)

  • it seems that it is more important here the order we ask for the numbers.

Maybe this is because are used to subtract when we have a larger number preceding a smaller number. Of course, to check this idea a bit better... an experiment with different numbers (other than 12 and 5) is needed.

Of course!

Tuesday 29 July 2008

Smelling or tasting? (ii)

So, last week end I made again the oil experiment with the help of a friend. It was very funny, sort of Coca-Cola/Pepsi contests.

The Idea: as in the previous experiment, the idea/belief to test is the following:

We cannot tell the difference between the taste of olive oil and sunflower oil just tasting them (so, closing our eyes and blocking our nose).

The material: Two cups, olive oil, sunflower oil and three coins (just two are shown in the photo).

The set-up: before starting to measure, we agreed three tries each. To avoid psychological advantage (I mean, thinking about my friend's behaviour in where she/he was going to place the cups with olive oil and sunflower oil could have provided some sort of advantage where taste was not the only thing measured), a coin decided where the olive oil was going to be placed: if the coin was a head, the cup with olive oil was to be placed on another coin that was lying on the table showing its head. Otherwise, the cup with olive oil went to the coin with the tail side up (actually we were no playing heads or tails, but heads or legs, as we used Manx pounds... ok, doesn't matter).

So, how can we accept or reject the result? If we flip a Manx pound six times, we can get:

  • three triskelions and three heads with probability ~31%, which comes from (6!/3!3!)*(1/2)^3*(1/2)^3 = 0.3125.
  • four triskelions and two heads (or four heads and two triskelions) with probability ~23%, as (6!/4!2!)*(1/2)^3*(1/2)^3 = 0.234375.
  • five triskeliions and one head (or five heads and one triskelions) with probability ~9%, result of (6!/5!1!)*(1/2)^3*(1/2)^3 = 0.09375.
  • six triskelions (or six heads) with probability 1/64 ~ 1.6%.

In short, this means that we have a chance of nearly 80% to get two, three or four triskelions. So, using a rather big significance level, we will accept as true the idea if we get this, and we will reject it otherwise (which would mean that we can actually tell the difference just tasting).

The measures: So, let's start the experiment!

Here are the two subjects:

apparently two normal individuals of Homo sapiens.

Subject A prepares before flipping the Manx pound...
I place the olive oil where the coin tells me.
Deciding after trying both oils.
After opening the eyes everything seems quite different!
After the three tries for subject A, subject B prepares to measure...
Subject B during one of the tries.
Subect B makes his decision.

The results: And after three tries each, we have got the results!

Which would be:

  1. Wrong
  2. Correct
  3. Wrong
  4. Correct
  5. Correct
  6. Wrong

Conclusion: This means we have got three wrong and three correct answers, more or less the same we would have got flipping a coin! Or, in other words, blocking our nose, we had no idea which oil we were trying, which means that, to the agreed significance level, the idea stated was correct.

Sunday 27 July 2008

Smelling or tasting?

I have seen I can summarize my philosophy about these small experiments in just one word: EMOTION, which means

  • Enjoy = fun!
  • Measurements = objectivity
  • Observation
  • Thought = we need a (specific) idea/belief to test
  • Incentive = we need a motivation
  • Originality = creativity
  • and the four Noes:

    1. No great, revolutionary ideas required
    2. Not a lot of time required
    3. Not a lot of material required
    4. Not a lot of knowledge required

So, the last weeks I have been quite busy, but that's just a cheap excuse (see the second no). The real reason I was not posting anything here is not time, it is just because I am not very used to it. Accepting it is the first step. The second step is doing something about...

So I will speak about a small experiment I did some weeks ago.

I was curious about the interaction between gustation and olfaction. Everybody knows that blocking your nose it is much more difficult to detect the flavour of everything, but I wanted to check this. I chose a specific idea to test:

I can tell the difference between the taste of olive oil and sunflower oil when I block my nose

So, to do this, and to make an objective measurement, I couldn't simply block my nose and try both oils, as my mind could still make me think I can tell something, just because I know the answer. I also needed not to know which one it was.

I put in two cups a little bit of each oil. To make it completely random, I closed my eyes and I asked my girlfriend to flip a coin. Then, she had to leave the cups in a place depending on the result.

After that, I tried one of the cups while blocking my nose. It was a very strange feeling! A viscous fluid in my mouth. No taste at all. It could have been bicycle oil. But I thought I still could tell something. So I tried the second cup (still nose blocked, eyes closed, of course). This was amazing: exactly the same sensation! (It might seem obvious, but making the experiment is really interesting, as you don't have to believe in that: you feel it).

Actually you can still "cheat", as olive oil seems to be more viscous than sunflower oil. But you have to practice a bit, and I didn't. So I went out on a limb and said something. I can't remember what I said, but I was wrong.

Then I did the same, but without blocking my nose. Even before trying the oil it was completely obvious which one was the olive oil. It was as clear as telling blue from red.

It was an interesting experiment. Maybe next time I will check if it is possible, with some practice, to tell who's who by their viscosity.

Saturday 24 May 2008

Results from the first experiment

Some 12 days ago I talked about what experiments are. Obvously I was not speaking about the sort of experiments that are done in a laboratory, but about the experimenting mind. My goal is having a more experimental behaviour, to be keen to learn things by myself, and not just from books. I want to listen directly to nature, and not just to the people who read about somebody who heard about the interesting findings of somebody else who was listening to nature.

Strictly speaking, an experiment needs more things than what I said: we need a depedent variable (which we have to measure), an independent variable (which must be the only thing that changes in the experiment); the experiment has to be reproducible, and so on...

But speaking about science is not science (is philosophy), and what I like is science, so I will not care too much about the details. I want to learn the details doing the experiments.

So, in my last post, which was also the first one, I made the following statement:

This post will get no more than three different reader's comments within the next seven days

I left more than seven days and... I was completely right! Not even one post. Obviously I didn't tell anybody anything about this blog. I didn't even leave links to this blog in any other website (until one hour ago or so). Otherwise, the experiment wouldn't have been valid.

I put a counter you can see on the right hand side where the visits to this blog are shown. During the twelve days, the only visits from anywhere outside Dublin seemed to be from somewhere in Switzerland (hi there!). But he/she didn't leave any comments.

So now I can say I know something, I am not just believing in something that might be wrong: there are so many blogs around, that most of them are read only by their creators. There are some exceptions with popular blogs, but if they are popular it is because people already know them. But if you don't say anything to anybody, nobody will read the stuff (at least the first twelve days!). I am OK with that, because I am writing to myself (as most of the bloggers, probably), but it is very interesting to confirm this idea.

So, now lets do more interesting experiments...

Monday 12 May 2008

What are experiments?

Hello world,

this is the first post of my first blog. I just would like to express how much I love understanding Nature, and the way I reach this understanding. All understanding is based on experiments. Without experiments, we would believe in things which are not true, and we wouldn't be able to predict how the Nature will react to anything.

I really enjoy doing experiments, but I don't do as many as I could, and I want to improve this. An Italian friend who lives in Finland once told me that Finnish people use to say "learn from inside" (understand) or "learn from outside" (learn by heart). I think I have been learning too many times from outside (books, other people, websites...), and now it's time to change that. I don't want to be a tourist of knowledge, but an explorer of knowledge, a creator of knowledge.

Sometimes, I think I have no time, or I convince myself that it is too complicated this or that experiment. But actually, we are surrounded by Nature. We are Nature ourselves, so... it can't be so difficult to make her a question.

So, what can I do to do more experiments, every time, everywhere? I first have to know what is an experiment, and what is not.

To do an experiment we do NOT need:
  • to have great ideas (great ideas are helpful, but not at all needed: we can do the simplest experiments about every day's life, so there is no more excuses such as "I'm too tired to think [about something complicated]" or "I have no imagination"),
  • a lot of time (this is not at all in the definition of experiment, an experiment can be done in a few seconds if we want),
  • a lot of material (an experiment can be done in a laboratory, and some "important" experiments require such conditions that a laboratory might be the only solution, but this is not true for all the experiments, and so it is not a part of its definition. An experimental mind finds beliefs to test everywhere),
  • a lot of knowledge (we can test the simplest thing we know, and doesn't matter if somebody knew that already, so here we have another excuse we will not use anymore: "I have to learn more things about the subject").
But we do need some things:
  • an idea to test (we have to define what are we pursuing, otherwise we will never reach our target, simply because there is no target. It can be a very simple idea, but we have to know which idea is),
  • creativity (if we don't try to do it differently, we always will get the same answer),
  • willing to have fun (it is supposed to be interesting, isn't it?),
  • observation of our environment,
  • objective measurements (when we don't measure what we are studying, we have a deformed version of the world in our mind, and the longer we don't do it, the more deformed it gets),
  • motivation (and this is one of the reasons if am starting this blog, because I know myself, and I know that having something to write about what I am doing boosts my motivation).
The first experiment I will do on this blog is checking something. There exist lots of blogs (on Wikipedia somebody says that something called Technorati is tracking more than 112 million blogs), so I will test this idea:

very few people will leave a comment here.

This is based on the following facts:

  1. I think very few people will find this blog,
  2. even if somebody finds it, the probability that somebody reads the whole post is even smaller,
  3. and even if somebody reads everything, not everybody will leave a comment.
So we have a sort of Drake equation which is multiplying tiny probabilities giving an even smaller probability. Let me know if I am right or wrong.

To measure this in the most objective way I can, and make it a bit more interesting, I will make a prediction. Let's say:

This post will get no more than three different reader's comments within the next seven days

And, if I am wrong, would you tell me what is your idea of what is needed and what is not needed in an experiment?