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An Analytical Approach to the Best and Worst Poasters

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Comments

  • Pitchfork51Pitchfork51 Posts: 6,128
    Standard Supporter 5000 Comments 250 Answers 500 Up Votes

    Is it better to make 10 posts that get 10 chincredibles each, or 2 posts that get 15 chincredibles each?

    Apparently making 6000 that get 3 chins and a flag from boobs each gets you 56th place.

    PurpleReignTierbsHsotBoobs
  • UW_Doog_BotUW_Doog_Bot Posts: 164
    Swaye's Wigwam 250 Awesomes 100 Comments 100 Up Votes

    Is it better to make 10 posts that get 10 chincredibles each, or 2 posts that get 15 chincredibles each?



    Best Poasters
    (Combined Chin/WTF Ratio)

    Worst Poasters

    Most Rec'd (Per Poast)

    Most Anti-Rec'd (Per Poast)

    Most Controversial(Most Rec's & Anti-Rec's)

    dncTierbsHsotBoobs
  • chuckchuck Posts: 1,610
    250 Answers 500 Awesomes 1000 Comments 500 Up Votes

    I updated the sheet to include @ExtraChrisB @PurpleReign @chuck @uw2010 @DoubleJDawg @BennyBeaver @ThomasFremont and @dflea . Congratulations!!!!!




































    YOU ARE ALL



    With the exception of @uw2010 who snuck into the top five but also had the ignominious distinction of also being the most benign poaster.
    Woohoo1!!!1! We're all winners!
    UW_Doog_Bot
  • dncdnc Posts: 30,580
    Standard Supporter 25000 Comments 250 Answers Fucktard of the Week Award
    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.
    UW_Doog_BotNeighbor2972TierbsHsotBoobs
  • Fenderbender123Fenderbender123 Posts: 1,347
    Standard Supporter 250 Answers 1000 Comments 500 Up Votes
    edited January 12
    dnc said:

    Is it better to make 10 posts that get 10 chincredibles each, or 2 posts that get 15 chincredibles each?

    It's better to LEAVE!
    This website would go bankrupt without my annual $25 donation.
    dncDerekJohnsonTierbsHsotBoobs
  • UW_Doog_BotUW_Doog_Bot Posts: 164
    Swaye's Wigwam 250 Awesomes 100 Comments 100 Up Votes
    edited January 12
    dnc said:

    none of this matters

    Hth
    dncTierbsHsotBoobs
  • SourcesSources Posts: 372
    250 Answers 500 Up Votes 500 Awesomes Third Anniversary
    chuck said:

    uw2010 said:

    Why do you hate @TheChart?

    Alts got cut. Ratios for most were outliers. Maybe i could do an alt bored ranking.

    Also, if you didnt make the 100+ list to be ranked then either poast more...or poast less.
    I'm not an alt:

    1600 posts.
    2600 upvotes
    1100 Chins
    80 down
    55 wtf

    I think that could have gotten me on the list, but fuck off.
    Nothing special.
    GrundleStiltzkinTierbsHsotBoobs
  • UW_Doog_BotUW_Doog_Bot Posts: 164
    Swaye's Wigwam 250 Awesomes 100 Comments 100 Up Votes

    dnc said:

    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.

    This flipside to this coin is that it takes a while to build a brand, so the old guard has more name brand recognition which leads to more chins and up votes.
    In statistics given a large enough sample we can assume that white noise is zero.

    ISSUE: What is white noise?
    WHITE NOISE: White noise is defined as the error term of a time series model distributed in the Gauss-Markov process in time series data set. Given a time series data where the Y is produced in a form of Yi: (y1, y2, …, y3) in a time series: ti:( (t1, t2, …, T); this time series event is denoted as yt or X(t). The model is given as:
    (1) yt = Bo + B1Xt + ei
    The focus of white noise is on the term ei in the equation. The ei is a set of ei: (e1, e2, …, eT) generated by each time series event. These elements of ei have the following three properties: identical, independent and mean zero distribution, i.e. N(0, var). In order to be white noise, the ei process must have the following characteristics:
    (2) E(ei) = 0
    (3) Var(ei) = sigma2
    (4) Cov(et, et-s) = 0

    TLDR The issues you bring up don't really matter because there are other issues that will probably cancel them out or drown them out over a large enough sample.
    YellowSnow
  • Pitchfork51Pitchfork51 Posts: 6,128
    Standard Supporter 5000 Comments 250 Answers 500 Up Votes

    dnc said:

    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.

    This flipside to this coin is that it takes a while to build a brand, so the old guard has more name brand recognition which leads to more chins and up votes.
    In statistics given a large enough sample we can assume that white noise is zero.

    ISSUE: What is white noise?
    WHITE NOISE: White noise is defined as the error term of a time series model distributed in the Gauss-Markov process in time series data set. Given a time series data where the Y is produced in a form of Yi: (y1, y2, …, y3) in a time series: ti:( (t1, t2, …, T); this time series event is denoted as yt or X(t). The model is given as:
    (1) yt = Bo + B1Xt + ei
    The focus of white noise is on the term ei in the equation. The ei is a set of ei: (e1, e2, …, eT) generated by each time series event. These elements of ei have the following three properties: identical, independent and mean zero distribution, i.e. N(0, var). In order to be white noise, the ei process must have the following characteristics:
    (2) E(ei) = 0
    (3) Var(ei) = sigma2
    (4) Cov(et, et-s) = 0

    TLDR The issues you bring up don't really matter because I'm a nerdy fag
    TierbsHsotBoobsFire_Marshall_Bill
  • BennyBeaverBennyBeaver Posts: 5,595
    5000 Comments 250 Answers Fifth Anniversary 500 Awesomes

    Worthless without pulling chInsightfuls and LOLs (RIP)

    GrundleStiltzkinTierbsHsotBoobs
  • Pitchfork51Pitchfork51 Posts: 6,128
    Standard Supporter 5000 Comments 250 Answers 500 Up Votes

    dnc said:

    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.

    This flipside to this coin is that it takes a while to build a brand, so the old guard has more name brand recognition which leads to more chins and up votes.
    In statistics given a large enough sample we can assume that white noise is zero.

    ISSUE: What is white noise?
    WHITE NOISE: White noise is defined as the error term of a time series model distributed in the Gauss-Markov process in time series data set. Given a time series data where the Y is produced in a form of Yi: (y1, y2, …, y3) in a time series: ti:( (t1, t2, …, T); this time series event is denoted as yt or X(t). The model is given as:
    (1) yt = Bo + B1Xt + ei
    The focus of white noise is on the term ei in the equation. The ei is a set of ei: (e1, e2, …, eT) generated by each time series event. These elements of ei have the following three properties: identical, independent and mean zero distribution, i.e. N(0, var). In order to be white noise, the ei process must have the following characteristics:
    (2) E(ei) = 0
    (3) Var(ei) = sigma2
    (4) Cov(et, et-s) = 0

    TLDR The issues you bring up don't really matter because I'm a nerdy fag
    I am 6'5" 260 lbs. Former Army Ranger and college basketball player. You really don't want any in real life. You are little more than a cowardly pussy.
    What the fuck did you fucking say to me you little bitch?
    PurpleReignjhfstyle24
  • UW_Doog_BotUW_Doog_Bot Posts: 164
    Swaye's Wigwam 250 Awesomes 100 Comments 100 Up Votes

    dnc said:

    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.

    This flipside to this coin is that it takes a while to build a brand, so the old guard has more name brand recognition which leads to more chins and up votes.
    In statistics given a large enough sample we can assume that white noise is zero.

    ISSUE: What is white noise?
    WHITE NOISE: White noise is defined as the error term of a time series model distributed in the Gauss-Markov process in time series data set. Given a time series data where the Y is produced in a form of Yi: (y1, y2, …, y3) in a time series: ti:( (t1, t2, …, T); this time series event is denoted as yt or X(t). The model is given as:
    (1) yt = Bo + B1Xt + ei
    The focus of white noise is on the term ei in the equation. The ei is a set of ei: (e1, e2, …, eT) generated by each time series event. These elements of ei have the following three properties: identical, independent and mean zero distribution, i.e. N(0, var). In order to be white noise, the ei process must have the following characteristics:
    (2) E(ei) = 0
    (3) Var(ei) = sigma2
    (4) Cov(et, et-s) = 0

    TLDR The issues you bring up don't really matter because I'm a nerdy fag
    I am 6'5" 260 lbs. Former Army Ranger and college basketball player. You really don't want any in real life. You are little more than a cowardly pussy.
    What the fuck did you fucking say to me you little bitch?
    What the fuck did you just fucking type about me, you little bitch? I’ll have you know I graduated top of my class at UW, and I’ve been involved in numerous secret raids with Anonymous, and I have over 300 confirmed DDoSes. I am trained in online trolling and I’m the top hacker in the entire world. You are nothing to me but just another virus host. I will wipe you the fuck out with precision the likes of which has never been seen before on the Internet, mark my fucking words. You think you can get away with typing that shit to me over the Internet? Think again, fucker. As we chat over IRC I am tracing your IP with my damn bare hands so you better prepare for the storm, maggot. The storm that wipes out the pathetic little thing you call your computer. You’re fucking dead, kid. I can be anywhere, anytime, and I can hack into your files in over seven hundred ways, and that’s just with my bare hands. Not only am I extensively trained in hacking, but I have access to the entire arsenal of every piece of malware ever created and I will use it to its full extent to wipe your miserable ass off the face of the world wide web, you little shit. If only you could have known what unholy retribution your little “clever” comment was about to bring down upon you, maybe you would have held your fucking fingers. But you couldn’t, you didn’t, and now you’re paying the price, you goddamn idiot. I will shit code all over you and you will drown in it. You’re fucking dead, kiddo.
    PurpleReignjhfstyle24TierbsHsotBoobsMad_Son
  • doogiedoogie Posts: 5,767
    5000 Comments 250 Answers 500 Awesomes 500 Up Votes

    dnc said:

    The only real flaw in this analysis is that chin's haven't always existed (nor have their predecessors "loves" I believe). There was a tim long ago on this here bored where the best response you could give to a poast you appreciated was an upvote. This almost assuredly suppresses the more tenured members of the bored's ratios.

    Of course, none of this matters so I wouldn't waste 53 seconds trying to figure out a workaround, just thought it was chintriguing and chinteresting chinformation.

    This flipside to this coin is that it takes a while to build a brand, so the old guard has more name brand recognition which leads to more chins and up votes.
    yeah. Yeah, that’s it. That’s what I’m doing here!
    UW_Doog_BotMad_Son
  • BearsWiinBearsWiin Posts: 2,440
    Swaye's Wigwam 250 Answers 1000 Comments 500 Awesomes
    Sources said:

    chuck said:

    uw2010 said:

    Why do you hate @TheChart?

    Alts got cut. Ratios for most were outliers. Maybe i could do an alt bored ranking.

    Also, if you didnt make the 100+ list to be ranked then either poast more...or poast less.
    I'm not an alt:

    1600 posts.
    2600 upvotes
    1100 Chins
    80 down
    55 wtf

    I think that could have gotten me on the list, but fuck off.
    Nothing special.
    Don't plagiarism my shit fucko unless I'm included in this fucking ranking.
    Pitchfork51TierbsHsotBoobsMad_Son
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