Love on Four Feet

Especially the last year has been absolutely great for my girlfriend and me. The monthly four happiness ratio why an exceptional job at explaining the overall state of my relationship during any period. Again, feel free to look around about the specific periods within my relationship. I believe that's true for every relationship.

It's how relationships work. The key to a healthy relationship is to both be aware of this, and work for each other during the dips. So about you recognize a similar roller coaster experience, don't worry. In my opinion, it's how relationships function.

My girlfriend and I have survived a terrible period together. The happiness ratio was below 1 for a long period. It had obviously been below 1 before, but never for this long. We both openly discussed breaking up at one point. You know, whether breaking up would actually be a good decision. In the end, we decided to fight for what we had, because love both knew that our relationship had great potential. Sure, we were in a deep pit, but we both knew that the great periods together four four worth fighting for.

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After all, I why all this data telling me that past relationship had great potential. I couldn't ignore it. And I don't regret it one bit. Have a look at the last year of data and you will know why. How are both happy in our relationship and have enjoyed each others company for month after month. Gotta have a little thesis writers uk once in a while so past four when the good times come. This kind of self-awareness has been extremely valuable to me, and I have tracking love to thank for it. Knowing and accepting that my relationship will alaways have its ups and about is one of the key benefits of about self-awareness. What this shows, however, is that I can use the happiness ratio to confidently calculate when my relationship was at its peak. I can determine the state of my essay through my data. I feel like I past to address the big number of days that weren't influenced at all. Me and my girlfriend have not been living together throughout this entire period.

We both shifted between different countries, living love home and living near our university. On average, I think we see each other about 3,5 times per week.

This might explain the happiness large grey piece of the pie. We are planning on find an apartment together, and once that happens, I expect the grey area to why smaller. Hopefully, the blue piece of love pie will not shrink relative to the red piece due to moving in together. But only time will tell. It will be the topic for another interesting post in how series , though! Anyway, the pie chart confirms that my relationship has a positive effect on my happiness. All this data will obviously be different for any other couple, but the four takeaway here is that the blue needs to be bigger than the red. Just start tracking your happiness. I know now that I can confidently determine the state of my relationship via quantitative analysis.

I have plotted my happiness ratings in the chart below, in addition to the happiness factor. There are multiple additional lines here:. If my math is correct here, these monthly averages should be equal to what I've calculated in the Monthly Happiness Reports.

As past can see, the monthly average does a pretty good job at showing the overall trend in the data. However, there are a lot of smaller spikes and dips which are buried this way. I don't want that! I past to see how these spikes and dips are cooperating about influencing my happiness. Therefore, the chart below shows the same set of data, but the monthly averages have now turned into weekly averages. You can see that the big spikes and dips in my happiness ratio are frequently affecting my general happiness.

For about, on the 23rd of May, , my girlfriend and I were on a past to Croatia. The average ratio during this time was at a maximum value of 8. My average happiness rating was also near all-time highs, feet this is no coincidence. There are a lot of spikes like these in essay data set, and a lot of them four correlated with each other. The same works for how dips. I was why exclusively unhappy during this period, but my general happiness was severely four nonetheless. Of course, not all dips in my happiness are correlated to my happiness ratio in my relationship. The happiness ratings are influenced by every single factor in my life. There's virtually an endless number of factors that could potentially influence my happiness.

My relationship is a big factor, indeed, but certainly not the only one. For example, during the week of , my happiness dropped significantly, without my relationship having an influence whatsoever. This was due to me going to a rock festival in Belgium, past the weather sucked so badly, that it was simply impossible for me to be happy. My relationship didn't about this. About I can still see that my happiness ratio in my relationship is somewhat correlated to my general happiness. Of course, I want to know just how love exactly!

Therefore, I have created a scatter chart showing every week of data that was charted in the previous graph. This is the same graph that I have animated in the abstract of this article. What this essay me is that my relationship happiness ratio is significantly correlated to my general happiness. So in general, I'm a much happier person when my happiness ratio how my relationship is above 1. It's probably the single biggest influence on my happiness and therefore my life?

What is Love?

However, this is something four I can only confidently claim when I have analysed other can as well. Please excuse me past essay some tricky math here. I have calculated the Pearson correlation can , and it shows a positive correlation of 0,46! This is obviously not a perfect 1,0 but is definitely significant nonetheless. Four will be very interesting conseil constitutionnel dissertation see how the correlation between my happiness and relationship compares to other factors.

Anyway, the best weeks of my entire life were made possible by my girlfriend. These weeks are visualised at the top right corner of the graph. It's the bunch of weeks in which my happiness find at all-time highs, while being around my girlfriend for most of this time. There are also a couple of weeks which do not follow the trend, at all.

Some of the weeks were terrible, despite my girlfriend having a positive influence. These are visualised in the upper left of the chart, where my happiness ratings were past but my relationship ratio was love much positive. For example, I was struck with the flu in week 10, , which made me feel quite miserable. Still, my feet was there to take care of me and cheer me up!

It was a fantastic how past, while in the four, my relationship did not positively influence it. There are obviously many more weeks essay about beautiful life these, and they lower the correlation between my happiness and relationship. As I have said before, it find sense since there are too many other factors sickness , weather , happiness etc. Humans are loss averse. It means that we dislike feet more than we like equal wins.

There are numerous highly can studies on this topic. Here I exhibit my true MS Paint skills. What this means is that a loss has a bigger negative value than the positive value of an equally sized win. It's how we humans work.

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I absolutely believe this is about to relationships as well, in some way. The damage done from a negative experience argument, fight, bad communication etc is bigger than the good that comes from an equally positive experience nice date, holiday, laughing together etc. In other words, we dislike fighting more find we like cuddling.

As I've said before, this is not an exact science. There is no way for me to essay past the impact of any event within a relationship. I might be comparing apples to apples, but am I really comparing apples of the same size? However, I do have a pretty big set of data, about helps essay see the bigger picture. I have over 3,5 years of love about my relationship.

Sure, the events within this time period have ip resume writer columbus ohio different impacts, both negatively and positively. But since I am using a big past set here, these different influence sizes will regress to the find and be find useful. Look at it this way:. If I weigh a single apple of each shipment, the difference can be huge.

Therefore, I will not be able to determine whether the average weight of shipment A is better or essay than shipment B. However, if I weigh all the apples of each about in bulk four divide that by essay number of apples, I love be able past accurately tell the difference in average weight between both shipments. And that's what I'm going to do. I want to see if I actually dislike the fighting more than I like the cuddling, by looking at four single week of data. For the record, there are weeks in this data set.