Score
Title
863
How To Search ELI5: A Quick Reminder About Rule 7
14228
ELI5: Why do cars travel in packs on the highway, even when there are no traffic stops to create groups?
33
ELI5: Why do human eyes show so much white while most mammals don't have much visible white of the eye?
6
ELI5: SD. SS. SA. Gestapo. Wehrmacht. Sipo. Kripo. What were they all and how do they relate to each other?
32
ELI5: How come smart phones can run intense games without a fan and still not burn the CPU, but a desktop computer can't even load the desktop for more than a few minutes without permanent damage?
4
ELI5: Why sliding a knife makes a better cut than just pressing it down?
6
ELI5: When and why did 8 hours of sleep become the standard for a solid night’s rest?
32
ELI5: Why is ?4 = -2 false?
116
ELI5: If we breathe in O2 and use the oxygen, how do we release CO2? The same ammount of oxygen we took in, just an added carbon atom
20
ELI5 So, Shrimp have 16 color rods, enabling them to see many more colors than us humans. Would there ever be a way (surgically or not) for us to see those new colors?
3
ELI5: Why does feathers contract when in contact with oil?
4
ELI5: Why do certain types of noise enhance our abilities to focus and study whereas others don't?
9
ELI5: Going off the idea that we never actually 'touch' anything how can something like a knife be sharp, is it just the magnetic field around it that's sharp?
4
ELI5: What is unique about Playstation 2 disks that prevents us from booting burned ISOs?
59
ELI5: What happens to dust particles that get in to the eyes and lungs?
7
ELI5: Other than simply not liking it, what biologically causes sudden loss of interest in something?
2
ELI5: does juice expire and how? Is it more about the taste goong bad or is it unhealthy to drink juice that has expired a few months ago?
3
ELI5: What is the biology behind being able to raise one eyebrow but not the other?
16
ELI5: Why does the sensation of having to pee come in waves of intensity, such as needing to pee one minute and then losing that feeling the next?
32
ELI5: How does a telephone plug work with both a phone and a modem? Is it the same data being transferred or is there multiple types of data being passed and the device decides which one it needs?
11
ELI5: The Indian caste system.
1
ELI5: What is multi level marketing?
63
ELI5: What is happening internally when a boxer 'loses his feet' ?
7
ELI5: According to the IMF, the world's debt has reached 225% of the world's GDP. How is this possible?
1
ELI5 - calorie partitioning and what we can do (if anything) to control it.
1
ELI5: How Scupper Holes work?
0
ELI5: Why are pre-prepared meals generally seen in such a negative light? Where is the line drawn between what is a "reasonable shortcut" when cooking or not?
1
ELI5:Why so many people in south east asia idolized half white people?
2
ELI5: Protons, electrons and neurons - how do they dictate an elements properties?
39
ELI5: Why do mirrors that are placed parallel to each other begin to tint green further into the reflection?
3
ELI5: Why is the grape Welch's fruit snack always tougher to chew than the rest of the flavors?
3
ELI5:The lagging strand during DNA replication and Okazaki fragments.
22
ELI5: Whatever happened to the "hypsilophodont" classification in dinosaurs? How do you classify those now?
1
ELI5: Why US legislation seems more "messy" than other first world countries? Or is it just sensationalized by the news media?
2
ELI5: why do RBC need energy/ATP?
2
ELI5: how are lasers used to measure distance so accurately, and why can it also track movement i.e. with a PC mouse?
15
ELI5: Why do women take the last name of their husband when the get married?
2
ELI5: How do you go about opening/starting a school
0
ELI5: why does the same 20 degree Celsius setting feels cool for cooling mode but feels hot for heating mode, while they are actually the same temperature?
3
ELI5: In real estate, what incentive does the buyer's agent have to keep the price down?
4
ELI5: Studying vs fun
3 Optrode I'm not familiar with "multivariate multidimensional scaling", but I can explain "multidimensional scaling" some. Multidimensional scaling (MDS) is a method for taking information about how far apart some points are, and arranging them in space so that they're approximately that far apart. The points could be anything: People, images, sounds, products on Amazon, books... Anything that you could define some kind of similarity measure for. Here's an [example](https://upload.wikimedia.org/wikipedia/commons/thumb/b/be/RecentVotes.svg/708px-RecentVotes.svg.png) from Wikipedia. The people who created this figure did so by taking all the members of the U.S. House of Representatives, and finding out how often they voted the same way on something. This is essentially a measure of how similar their stances are: If two representatives voted the same way 95% of the time, they probably have pretty similar stances, but if they voted the same way only 30% of the time, their stances must be pretty dissimilar. Then they applied MDS, which found a two-dimensional arrangement of where to put each representative, so that the distance between two points in that 2-D plot is as close as possible to matching how dissimilar their voting patterns are. MDS has limits, because sometimes it's impossible to accurately capture how close/far apart all the points are in only 2 or 3 dimensions. Take, for example, 8 points that form a cube. There is no possible way to plot those 8 points in 2 dimensions so that all of their distances from each other in that 2-D space are the same as their original distances to each other. In more "nuts and bolts" terms, MDS usually takes as an input a "distance matrix", which is a N by N matrix of numbers (where N is the number of data points you have) where, say, the 8th column of the 4th row is 'how dissimilar is point 8 from point 4'. And MDS will spit out a set of coordinates in 2-D (or 3-D or whatever you want) that roughly corresponds to how far apart those points are.
3 0 Optrode I'm not familiar with "multivariate multidimensional scaling", but I can explain "multidimensional scaling" some. Multidimensional scaling (MDS) is a method for taking information about how far apart some points are, and arranging them in space so that they're approximately that far apart. The points could be anything: People, images, sounds, products on Amazon, books... Anything that you could define some kind of similarity measure for. Here's an [example](https://upload.wikimedia.org/wikipedia/commons/thumb/b/be/RecentVotes.svg/708px-RecentVotes.svg.png) from Wikipedia. The people who created this figure did so by taking all the members of the U.S. House of Representatives, and finding out how often they voted the same way on something. This is essentially a measure of how similar their stances are: If two representatives voted the same way 95% of the time, they probably have pretty similar stances, but if they voted the same way only 30% of the time, their stances must be pretty dissimilar. Then they applied MDS, which found a two-dimensional arrangement of where to put each representative, so that the distance between two points in that 2-D plot is as close as possible to matching how dissimilar their voting patterns are. MDS has limits, because sometimes it's impossible to accurately capture how close/far apart all the points are in only 2 or 3 dimensions. Take, for example, 8 points that form a cube. There is no possible way to plot those 8 points in 2 dimensions so that all of their distances from each other in that 2-D space are the same as their original distances to each other. In more "nuts and bolts" terms, MDS usually takes as an input a "distance matrix", which is a N by N matrix of numbers (where N is the number of data points you have) where, say, the 8th column of the 4th row is 'how dissimilar is point 8 from point 4'. And MDS will spit out a set of coordinates in 2-D (or 3-D or whatever you want) that roughly corresponds to how far apart those points are.