60% of people drop out[0] - before you knew this, you had an 60% chance of dropping out. Now you know the statistics, you can go about exerting effort to end up in the 40% that don't drop out. And that number - 60% to 40% - tells you a little bit about how much effort you're going to need to put in (not much).
90% of startups fail[1] - now you know that, you want to put yourself in the 10% that don't. 90% to 10% is a bigger gap to jump than 60 to 40, so it's going to be a lot harder.
The author writes as if, when a 'real person' makes a recommendation, they aren't just making a prediction from data. The difference is that we can see how the algorithm works, whereas our picture of what the human brain does when it thinks about what someone might like is very murky.
And even if trusting a recommendation causes a placebo effect that increases the perceived quality (as others have pointed out, it seems plausible that a hyped recommendation may cause disappointment instead), why on Earth would we trust a process we don't understand, but mistrust a process we do?
We got used to it with laptops (think back to when they were mostly desktops - "I have to charge my computer?") and we'll probably get used to it with cars, assuming the same value to be gained is there (probably is).
tl;dr: They take too long to charge so clearly nobody should wait 58 minutes instead of 46 or whatever.
Hell, why even bother charging for 46 minutes? Charge it for however long you estimate it takes you to fill up the gas in your other car, and complain when the car runs out then, too.
Not a good piece at all; can't say whether that reflects on the author too or this is just him/her being mindkilled over, of all things, charging time.
The point is that the author /did/ charge the car sufficiently. The car told him he could make each leg of the trip, and why would he waste an hour to charge the car completely? It would be silly to not spend 30 seconds to finish filling up a gas tank, but -- in my opinion -- it is perfectly reasonable to fill up an electric car to 50% above the necessary range and spare yourself significant waits.
Maybe a 58 minute charge at the last leg would've spared him the tow. But how could he have known? He had 125 miles to drive. He took the car to 185 miles of battery power.
That's like saying "I put just enough gas in the car to drive to the next station. I don't know how I ran out of gas early!"
There are a lot of factors in driving range. Tesla should be more conservative on their estimates, but realistically you don't fill a car just enough to get to the next station. And you definitely don't ignore low fuel warnings (even if you should have gotten a longer range.)
I'm not saying Tesla is perfect, but I do believe the NYT author wrote the article to make the car look bad to the average reader.
Agreed, instance_eval is definitely disgusting, but this trick scores well on readability, it's no more of a trap than some other Ruby idioms, and it serves a good purpose (robustness!).
def foo(bar, baz=(default = true; 'default'))
# it still looks separated from other arguments
if default
puts "#{bar}.times { puts #{baz} }"
else
bar.times { puts baz }
end
end
To anyone who knows more Ruby than I - is there a good reason against that I'm missing?
> To anyone who knows more Ruby than I - is there a good reason against that I'm missing?
I probably know less Ruby than you but these are my thoughts.
1) I took me a while to work out what was happening but I finally figured out that the default value is only evaluated when the argument isn't present.
2) If the default value is indicated in the docs it would be wrong for the function to behave differently depending on whether that default was relied on explicitly sent. If you need to know this you are probably doing something wrong elsewhere.
It's all well and noble to say "health journalism is flawed, everything is breathlessly reported as a breakthrough", but when you put Tara Parker-Pope and Gary Taubes in the same category, you're committing more of the same mistakes. There's nothing noble at all in shooting down all of health journalism.
He goes on to say:
"Worse still, health journalists are taking advantage of the wrongness problem. Presented with a range of conflicting findings for almost any interesting question, reporters are free to pick those that back up their preferred thesis."
It appears that this author's preferred thesis is that when presented with conflicting evidence, one should throw one's hands up in despair and do whatever you want ("apply common sense liberally"), instead of some kind of analysis of the evidence to find which side of the conflict is more reliable.
90% of startups fail[1] - now you know that, you want to put yourself in the 10% that don't. 90% to 10% is a bigger gap to jump than 60 to 40, so it's going to be a lot harder.
0,1: not actual statistics