Alice Adams has a BA in Philosophy from the University of Bristol and an MA from the University of Manchester, and since a stint as an analyst in the City has had fiction published in various places including The Times and Dark Mountain. This is her first novel. She lives in north London but escapes into the wilderness as often as possible.
RT @QuilletteM: The Case Against Factory Farming
by @Alice_Adams - 23 hours ago
RT @MotoClark: @Alice_Adams In my top three all-time examples of "how disappointing this isn't a euphemism".
by @Alice_Adams - yesterday
@MotoClark I await your poems ;)
by @Alice_Adams - 2 days ago
RT @MotoClark: @Alice_Adams I swear anyone spending long enough here could be another Thomas or Hughes, the two sons of Laugharne who used…
@MotoClark ❤️ *packs bag*
AliceAdamsAuthor - 8 days ago
Un petit bijou, vous ne pouvez pas passer à côté : Un été invincible
AliceAdamsAuthor - 9 days ago
'"It's less weird than the first idea, but it's still fricking weird,” says Norman Yao, a physicist at the University of California, Berkeley.'
AliceAdamsAuthor - 11 days ago
'Statistical significance is a concept underlying a huge amount of science—not just psychology or social sciences, but medicine, life sciences, and physical sciences, too. “Significance” used in this way doesn’t mean the importance or size of a finding, rather it's the probability of that finding showing up in your data even though your hypothesis turns out to be wrong.
If you have a hypothesis—say, reiki helps pain management—you’ll get two equivalent groups of people with pain problems, give one group reiki, and the other group some kind of placebo treatment. Then you’ll see how they all feel after the treatment and if there’s a difference between the two groups. If you’re right about your hypothesis, you should see a difference between the groups. If you’re wrong, and reiki doesn’t help, there shouldn’t be a difference.
The problem is that people are variable, so there will always be some degree of difference between two groups. What we want to know is the following: if you’re wrong, and reiki doesn’t help with pain, how likely is it that you’d be seeing the difference you get in your data? If reiki is useless, it would be extremely unlikely that you’d see a big difference between the groups, so it would be fair to take a big difference as evidence that reiki does help.
The problem is that sometimes, you'll get a big difference even if reiki is useless—that’s just how probability and human variability work.
Currently, many fields have the same threshold for acceptable evidence: you’d be able to use your study as evidence if you calculated that your data would have less than a 5-percent chance of occurring if reiki were useless. That 5-percent threshold is the p-value: if p is less than 0.05, that's statistically significant. If it's larger, it's not.
The 5-percent threshold was always an arbitrary cut-off, proposed by statistician Ronald Fisher in 1925. A chance of 5.1 percent is not objectively more meaningful than a chance of 4.9 percent. Fisher acknowledged that it was arbitrary, and he emphasized that it should be used carefully and in conjunction with other information to reach a sensible conclusion. There are already fields (like physics and genetics) that have different thresholds.'
AliceAdamsAuthor - 16 days ago
'Yes, I’m scared, but not all the time. When I was first diagnosed, I was terrified. I had no idea that the body could turn against itself and incubate its own enemy. I had never been seriously ill in my life before; now suddenly I was face to face with my own mortality. There was a moment when I saw my body in the mirror as if for the first time. Overnight my own flesh had become alien to me, the saboteur of all my hopes and dreams. It was incomprehensible, and so frightening, I cried.
“I can’t die,” I sobbed. “Not me. Not now.”
But I’m used to dying now. It’s become ordinary and unremarkable, something everybody, without exception, does at one time or another.
It was a feeling like no other, in late 2011, to hold a copy of my first novel in my hand. When Patricia Highsmith’s publisher sent her copies of her first novel, “Strangers on a Train,” she couldn’t believe how much space they occupied. It seemed so brazen to have made an object that took up room in the world. I knew what Highsmith meant. I’d stuck my neck out at last, staked my claim to be taken seriously as a writer, and here in my hand was the proof. Now, I thought, I can die happy.
To say that family has been my other chief priority in life is to understate the case. Marriage, children, the whole catastrophe, as Zorba called it. To become a mother is to die to oneself in some essential way. After I had children, I was no longer an individual separate from other individuals. I leaked into everyone else. I remember going to a movie soon after Nat was born and walking out at the first hint of violence. It was unbearable to think of the damage done. I had never been squeamish in my life before, but now a great deal more was at stake. I had delivered a baby into the world. From now on my only job was to protect and nurture him into adulthood, no matter what it cost me. This wasn’t a choice. It was a law.
That makes it sound like a selfless task, but it wasn’t. I got as much as I gave, and much more. The ordinary pleasures of raising children are not often talked about, because they are unspectacular and leave no lasting trace, but they sustained me for years as our boys grew and flourished, and they continue to sustain me now. I can’t help but take pleasure in the fact that my children are thriving as I decline. It seems only fitting, a sure sign that my job in the world is done. It’s like the day Dan, then in the fourth grade, turned to me twenty yards from the school gate and said, “You can go now, Mum.” I knew then that the days of our companionable walks were over, and that as time went by there would be further signs of my superfluity, just as poignant and necessary as this one.'
AliceAdamsAuthor - 17 days ago
Spent years when I worked as an analyst feeling faintly uneasy about the way even other analysts talked about p-values, and feeling like p<0.05 was kind of arbitrary though no one spoke as tho it was. Now they're are the heart of the current reproducibility crisis in science.
Here's a great article explaining it all. P-values, baby. You know you want to.
'Again: A p of .05 means there’s a less than 5 percent chance that in the world where the null hypothesis is true, the results you’re seeing would be due to random chance. This sounds nitpicky, but it’s critical. It’s is the misunderstanding that leads people to be unduly confident in p-values. The false-positive rate for experiments at p=.05 can be much, much higher than 5 percent.
In a 2013 PNAS paper, Johnson used more advanced statistical techniques to test the assumption researchers commonly make: that a p of .05 means there’s a 5 percent chance the null hypothesis is true. His analysis revealed that it didn’t. “In fact there’s a 25 percent to 30 percent chance the null hypothesis is true when the p-value is 05,” Johnson said.
Remember: The p-value is supposed to assure researchers that their results are rare. Twenty-five percent is not rare.'
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