Cueball is trying to explain his love using science for a valentine card. His attempts to analyze his feelings with charts and graphs reveal to him that his happiness and romance with the recipient are declining, which presents him with a choice: Will he be a scientist and accept data that he doesn't like and publish it, or will he be romantic, and just make a cute card. He decides that he is a scientist, resulting in a sort of anti-valentine.
- I wanted to make you a science valentine
- with charts and graphs of my feelings for you.
- [A graph shows romance and happiness. Romance cuts off, :indicating a breakup before the meeting of the narrator and his current SO, and happiness dips accordingly.
- A line indicates where the couple first met; romance is jagged thereafter, initially upwards but later down.
- Happiness climbs slightly more steadily and then dips again.
- More lines indicate a period of dating and then one of engagement.]
- and the happiness you've brought me.
- But the more I analyzed
- [The narrator works at a computer]
- r_0 = 0.20
- r_1 = -0.61
- r_2 = -0.83
- the harder it became to defend my hypothesis.
- In science, you can't publish results you know are wrong
- and you can't withhold them because they're not the ones you wanted.
- So I was left with a question: do I make graphs because they're cute and funny,
- [The narrator sits, looking at a sheet of paper.]
- or am I a *scientist*?
- Enclosed are my results.
- I hope you can find somebody else
- [A jagged, declining graph is superimposed over a red heart.]
- to be your valentine.
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If he really did figure out, by sitting down and thinking his life and their relation through, that he doesn't really love her, then he did the right thing. Of course he may not have been scientific enough, if the reasons his feelings and happiness decreases is caused by some outside agency... --Kynde (talk) 11:56, 29 April 2015 (UTC)
I think the r0, r1, r2 are correlation coefficients. They are all between -1 and 1, and all called r, which is a common name for a correlation coefficient. Also, this would mean r2 shows a strong negative correlation between two things. --184.108.40.206 06:57, 11 May 2015 (UTC)
I agree with the above comment, great explanation for this statistical variable which shows that his love becomes negatively correlated with time, complementing the first panel's graph. Barrtender (talk) 14:26, 16 September 2015 (UTC)
- I also think that the correlation coefficient interpretation is right. Moreover, it looks like r0 refers to the time just after the first meeting (slightly positive trend), r1 to the time when they were dating (negative trend) and r2 to the time after engagement (with even stronger negative trend). --220.127.116.11 18:26, 3 December 2015 (UTC)
- You are conflating correlation with slope. While they share the same sign, a gentle slope and steep slope can have the same correlation coefficient. It might be better to look at the correlation probability, which for the three values are 4.0%, 37.21%, and 64.0%. All other things being equal, these are the probabilities that the two variables are actually correlated. Thus, only the last measurements should be considered significant. It does not imply A strong negative trend. --Rhmcoff (talk) 04:59, 26 May 2017 (UTC)
Maybe 833: Convincing would be worth mentioning in the explanation, where Megan draws a relationship themed graph (and Cueball complains about missing axis lables) -- Ruffy314 (talk) 02:35, 3 November 2015 (UTC)