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Duc2000 last won the day on August 25

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About Duc2000

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    2nd best duck
  • Birthday 04/30/2003

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  1. So, it's been 2 days, I'd say that's long enough to get results. How many did we get? Well, 15. Not as many as last time. That's okay. I'll admit this topic was considerably less interesting. In fact, there aren't much things I find more interesting than traps. Ahem. More to the point, let's look at the data. 15 individuals responded to the voluntary survey. Two questions were asked: "How many games do you own?" and "What is your average monthly income?". As these are both clear quantitative variables, we can find the correlation between the two using the formula for r, the correlation coefficient. The equation is: r will always be a value between -1 and 1. A positive value for r means the two variables have a positive relationship, aka, as one increases, the other increases, and as one decreases, the other decreases. A negative value for r means the two variables have a negative relationship, aka, as one increases, the other decreases, and as one decreases, the other increases. If you ignore the sign on r and look only at the number, you can see how strong the correlation is. Values for r that are closer to 1 indicate a stronger correlation. The closer you get to 0, the weaker the correlation is. Also, in this case, X is the explanatory variable, the variable that causes a change in the other variable, and y is the response variable, the variable that is changed. The X and y with lines over them are the average for x and y, respectively, and the Sx and Sy are the standard deviations for x and y, respectively. Confused yet? Sorry. That's probably too much for most people. tl;dr r is a number that tells you how clustered together the data is and in which way the relationship is. I'll explain it after we get our r (which I'll use excel to calculate because plugging 15 values for x and y into that equation is not fun). For the explanatory (the x) variable, I used average monthly income, and for the response (the y) variable, I used number of owned games. Putting all our values on a scatter plot, this is what it looks like: For the time being, we'll assume that the person with an income of 10,000 isn't trolling, as I have no idea if they are or aren't. Anyways, now that we have them on the scatter plot, we want to do 2 things: get a line of best fit (Least Squares Regression Line for you Statistics nerds out there) and get the correlation. The line of best fit has a few formulas for it, but I don't feel like going over them and that would confused more people. tl;dr the line tries to predict y based on x, i.e. in this case it would predict owned games based on average monthly income. So here's the line: The equation for the line is y = -0.0055x + 119.03. Let's say we wanted to guess how many games someone who made $1000 per month had. We would plug 1000 in for x to get a predicted value of 113.53 games (114 since you can't have .53 a game unless it was made by Bethesda). Is this value a good prediction? This is where the R2 value you see in that graph comes into play. R2 is just R... squared. But it tells us the percent of the variation in the response variable (owned games) that can be accounted for by the best fit line. In this case, R2 is 1.8%. What this means is that the line is a terrible predictor of the games owned. Why? Because the actual correlation here is very low. If you look at those points, they are spread out a lot. If we take the square root of R2, we get r, which is .14 (hah, I avoided using the formula). Also, we know the correlation is negative because the slope of the best fit line is negative, so r is actually -.14. What do we know? We know that the correlation is incredibly weak and negative. AKA, the higher your income, the fewer games you're likely to own, except not really because the correlation between the two is weak. Just look at all those people who get $0 per month and own a few games. Ok, so what did we learn here? Not much. It was cool to see an actual negative correlation, meaning that maybe people are as bad with money as me, seeing as it suggests people with less money buy more games, but the weakness of the correlation makes it moot. Some possible errors within this: well, for starters, the person who makes -$58 for month, unsure if they were a troll, and the one who made $10000 a month, unsure for them to. Maybe y'all are that poor and that rich. Also, the data isn't all that linear, so correlation may not be that appropriate here, and more importantly, the data consists of a lot of people who make $0 per month, which I guess I should've expected. It means that it's basically all over the place, and so there really isn't much correlation. If we removed Mr. Moneybags making $10k, the correlation would probably disappear entirely. Welp, that was nice. It's difficult to get good data, seeing as I need volunteers (which biases it) and people don't visit here that often. So yeah, the data was probably biased and the findings not very significant, but I don't care, at least I've found other people who buy a bunch of games on very little a month. See ya! I haven't bought any games in months and I've barely played any too. Actually, now I'm buying anime figures, but I guessed that I would get even less data if I asked how many figures people owned. Oh well.
  2. It was moderately successful. I made an analysis of it here: They're both just for curiosity, and also maybe so I can feel less bad about buying so much stuff
  3. Alright, it took a bit for me to thing of what this one would be because I was trying to come up with quantitative variables so I could do actual correlation. What did I come up with? Average monthly income vs. number of games owned. Why, you ask? Because while logic would dictate that those with more money would buy more games, I want to see for sure. I also want to see if there will be outliers or people that make the relationship more curved than linear. Because I have a low monthly income, yet I own a relatively high amount of games. I'm bad with money. Let's see if other people are too. Take the survey here.
  4. Either the PS1 or a Nintendo DS; I can't remember which we got first.
  5. I don't know how you can even put SAO and Clannad in the same sentence. That's like, a cardinal sin. Clannad is legitimately one of the most emotional anime ever, and SAO is just bad. I don't mean to be rude; I know it still has some appeal to people, but seriously, am I tired of people defending SAO. It's just bad. It was boring when I tried to rewatch it because I knew then that there were no stakes, no good characters, nothing worth investing in the show. If you still get enjoyment out of it, that's fine, I'm not saying you shouldn't enjoy stuff you enjoy. I'm just ranting about SAO again because that's what I do. My recommendations are: For Rom Coms: Gamers (If you don't mind a lot of misunderstandings and no second season even though it deserves one), Kokoro Connect + the OVAs (THIS ONE DESERVES A SECOND AND A THIRD SEASON EVEN MORE THE SOURCE MATERIAL IS SO GOOD), Kaguya-Sama: Love is War (Extremely funny and actually gets more seasons) For crying: Anohana, Angel Beats, Clannad, Your Lie in April (Probably my personal favorite anime, although really it might be a tie between it and a few others) I could have more categories, but I'll leave it at those 2 since Saizy mentioned Rom Coms (Although I admit that crying is sort of the antithesis of comedy). Finally, as a response to everyone who mentioned SAO: Watch SAO Abridged. It's an incredible anime. Better by thousands of times than the original SAO. It surpasses it in story, character development, and, of course, comedy. https://www.youtube.com/playlist?list=PLuAOJfsMefuej06Q3n4QrSSC7qYjQ-FlU There's a link to it now go watch it. I promise you'll enjoy it.
  6. The data analysis is up! Thanks to all who took the survey! I got a lot more responses than I expected, actually. More than I did for my actual AP Research project.
  7. I decided that a day was long enough to get a good amount of responses to the survey I posted yesterday. If you didn't know, the survey asked questions regarding personal opinion of traps and some demographics. There were responses from 48 individuals, 3 of whom were tossed out due to joke responses. You let people enter their own gender, and you get this... So, let's get into some fun graphs! General Demographics First, just an overview of the demographics of the sample population. The population obviously is not a representative sample of GFL; it's just people who volunteered to take a survey on traps. Figure 1 is a pie chart for the genders of the participants. Figure 1 There were 3 females, 39 males, 2 who answered "prefer not to say", and 1 non-binary individual. This obviously already skews the data, as without a large number of female participants, we can't say for sure if the data accurately represents females within GFL (except for if there is an equal percentage of females within GFL as in the study, in which case... that would make a lot of sense). Figure 2 is a pie chart of ages. Figure 2 There were 5 participants who were 12-14, 16 who were between 15 and 18 (yes, I do know I technically put 18 twice. get over it), and 24 people who were 18 or older. This is actually a relatively nice spread between the three compared to the gender chart. My reason for using these three age ranges was because they're about the age you are in middle school, high school, and out of primary education, at least in the US. I wondered if the different atmospheres of each of this ages/school settings could be associated with opinion of traps, but we'll get there in a moment. The final pie chart for general demographics is Figure 3, a chart of sexuality. Figure 3 I'm not surprised by these percentages: 27 heterosexual individuals, 13 bisexual or polysexuals, 3 homosexuals, and 2 "Other". I apologize if you were confused by homosexual being there because you believe bisexuality falls under homosexuality. It technically does, but I believe that most people just use homosexual as another term for gay or lesbian. A quick addition: Figure 3.5 shows the percentage of people in the sample population who like traps. Figure 3.5 Nice to see that slight majority. We love traps. Anyways, on to the actual analysis: Analysis My methodology for analysis was forming segmented bar graphs, as each question asked a qualitative question. These graphs would have a demographic as each bar and the frequency for the 2 non-demographic questions as the segments. Figure 4 is the first graph, opinion on traps by gender. If you don't know how to read a segmented bar graph, each bar represents 100% of the individuals in that category. For example, the bar for females represents 100% of the 3 females in the study. The bar is then divided based on responses from those individuals: in this case, 33.33% of female participants believe traps were sexually attractive, and 66.66% believe they aren't. Figure 4 Based on the data in figure 4, males within the sample population are more likely to like traps than females are to like them. To be honest, that's mostly expected. Traps, after all, look feminine, and are designed to cater to a male audience, regardless of their sexuality. However, with only 3 female participants, I'm unsure if this really represents the majority of females in GFL. But As for "prefer not to say" and the Non-Binary individual, I definitely can't say anything about them. The number of people in each group was too small for the data to mean anything. Figure 5 shows the opinion on traps separated by age group. Figure 5 The graph suggests that there is an association between age and not liking traps: 18+ individuals are less likely to be attracted to traps than those under 18 within the sample population. Obviously this could be because of the sample size and non-randomness, but it's still nice to see trends. Figure 6 is the opinions on traps separated by sexuality, probably the most important graph. Figure 6 Well, these numbers aren't too surprising. Bisexuals and Polysexuals were way more likely to like traps than heterosexuals. I guess a few of you heterosexuals just have good taste. I'm a scientist, can't put bias in the presentation of the data. Anyways, homosexuals... actually weren't likely to be attracted to traps. 0% probability that they would be, in fact. Is that because of the combination of both male and female characteristics? Do they just want 1 or the other? That would make sense, but I can't say for sure. The graphs just show association. Also, there were only 2 homosexual individuals in the survey population, so that data could be heavily skewed. Maybe homosexuals actually all love traps and we just didn't survey the right ones. Again, the non-randomness of the sample comes into play. Also, all individuals who put "Other" for the sexuality liked traps. While there are only two of them, I guess it would have been interesting to know what the sexuality actually was so we could see if that affected it. Figure 7 is the first graph looking at knowledge of the dick, separated by gender. Figure 7 Essentially, this was asking if you thought the trap was more attractive with or without the dick. Figure 7 shows that females were most likely not to care, likely because the females just didn't like the traps in general. For males, none of the options were over 50%, but the appeal decreasing was the highest percent. This goes back to Figure 4: we can see that about the same percentage of males who didn't find traps attractive also said the dick made the appeal decrease. Does this mean that the obvious is true, and that males don't like traps because it has a dick? Why yes Duc, and why did you spend so much effort to reach that conclusion? Because I felt like it. Anyways, based on the raw data alone, males were more likely to not like the trap having the dick than any other gender, including "Prefer not to say" and non-binary, but remember, every gender but male had a low number of individuals, so the data doesn't really mean anything. Figure 8 is a graph of knowledge of the dick and appeal based on that by age. Figure 8 The values here were all about the same. There's no association between age and the effect a trap's dick has on your perceived appeal of said trap. Pretty unsurprising. Figure 9 is the final segmented bar graph, a graph of sexuality and whether the dick affected the appeal or not. Figure 9 So, unsurprisingly, heterosexuals were most likely to not like the trap having a dick. When you consider that statistically, most of them were male, it makes sense. There's almost an equal percent of bisexuals/polysexuals for whom the appeal stayed the same and increased. So about half of them like the trap more because of it, and half don't. Homosexuals were likely to maintain the same view of the trap regardless of the dick, and "other" don't like dicks I guess, even though they liked traps... Conclusion Is any of this data useful? Not really. I just felt like collecting it. Overall, we learned things we already guessed: bisexuals like traps and heterosexual (likely males) don't. Older people don't like traps. And when it comes to bisexuals, their opinion on the dick is (based on Figure 9): Now, we can't explain these findings with the data gathered. We can only guess at why older people don't like traps (hmmm maybe the data is skewed just a thought though). All the data shows is association, not causation or really even correlation (you need quantitative variables to talk about correlation). So, thanks to all who participated! I'll try to do another one of these soon, hopefully with a quicker data analysis.
  8. I'm conducting a brief survey for people within GFL ANYONE WHO SEES THIS POST. Why, you ask? Because I like looking at data and analyzing it, especially after I've started AP Statistics this year. So I'll be quick: This first survey is on traps. Are they your thing, or not? I don't care about whether they are gay or straight; that question has been looked at to death. Rather, I just want to know what people think of them, and then I'll plot that with demographics on a segmented bar graph to see if associations emerge. It's highly likely that the data will lean immensely towards people not liking traps, so... that might be an annoying hurdle. The survey is completely anonymous to me and to the rest of humanity, so feel free to give answers that you might not normally say aloud. It'll probably take a minute max to complete. You can take the survey here. Thanks! Please take it so I don't feel sad at having 0 data points
  9. Happy birthday!

    I'm late, aren't I? Damn you, time zones.

  10. I know, but I assume in an infinite universe there is the required technology to both extend human life and make me sleep indefinitely while I travel
  11. I'm hoping there is a lot of transparency then, so that a failure to meet expectations can be seen. I don't mean to focus on myself, but I can see something like what happened with my resignation from Breach happenng: I admitted everything I had done wrong, and most people focused more on the few things that I'd done right. I think that's mostly because they didn't know the full extent of what went on. All the promises I made to myself, all the plans I had, and my ultimate failure to never do them and just sit around being inactive, doing other things. Maybe it was a case of my friends being kind or me being too harsh on myself, but I still think the lack of transparency made it hard to see the full effect of me being a poor manager, so they weren't harsh on me in any sense of the word. But look at the new Breach manager and you see am instant difference: stuff being added and worked on everyday. You can tell that they're effective. But if someone isn't being effective, it's harder to notice without any transparency. What were they supposed to be working on, and is it obvious that they aren't working on it? Maybe this isn't relevant to the topic of responsible Community Representatives and I'm just rambling. Either way, I just wanted to say the obvious: Transparency is important.
  12. You can use the teleporter. I'll find a way to travel around the universe that doesn't involve killing me and making a clone. To be fair, with a universe like this, there exists somewhere in it a ship capable of moving at like 99% the speed of light, so I just have to screw about with other propulsion methods until I come across it. And, if our current science is wrong and moving beyond the speed of light is possible, then I could also find a ship that moves at those speeds within this same universe.
  13. After about 7 total hours of working, the Unravel cover is done.








    It turned out to be 9 pages, although it will still take the same amount of time to play as the Animenz version does (the tempo and number of measures are the same).






    I hope I've made it easy enough for me. It would be ironic to have done all this work and still just not be skilled enough at piano. But I'm trying to improve!


    I exported it to a PDF so I can print it tomorrow and start work. Right now, it's bed time.

    1. Beaker


      Music man. 

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