#math530 journal #5
This is a really cool statistic about the recent election. The ages were completely divided. I wonder why age division wasn't a thing in the early 2000s. And with this division, it's going to be interesting to restudy in the 2020 election.
The age divide in voting – which barely existed in the early 2000s – is large in this year's midterms in the U.S. Majorities of voters ages 18 to 29 (67%) and 30 to 44 (58%) favored the Democratic candidate. Voters ages 45+ were divided. https://t.co/BlLcqFklc6
#math530 journal #4
Interesting statistic from Pew. Makes me think about how online learning is affecting students, because while it's really helpful, it's pretty expensive and people forget that. I'm wondering what sampling method they used for this? And what types of schools?
35% of U.S. teens say they often or sometimes have to do their homework on their cellphone, and this is especially the case among lower-income teens. https://t.co/3yzTAz6VWB
#math530 this podcast discusses issues surrounding the 2020 US Census, specifically how Latino and other minority groups can be underrepresented...pretty crazy because the problems take a mini lesson back into US history
https://t.co/NqiFYRnTiD
#math530 journal #3
This is really interesting data about comprehension of US facts/opinions by age...wondering how they collected the data but super relevant and interesting :)
Younger Americans are better able than their elders to correctly classify factual and opinion statements that appeal to the left and right https://t.co/vFKA5Qf5eV
#math530 changing my LinReg project topic:
Now I'll be researching the correlation between life expectancy and enrollment into secondary schools per country
Can you spare 20 mins daily after reading the statistics below? Stop by our library today for the book fair and get a jumpstart on reaching these goals with your child. #bookfair#scholastic#library#reading#literacymatters
Facebook, Google and Twitter have new tools that attempt to shed light on dark ads — those online political messages that keep people in the dark about where they came from.
Here’s what those databases can — and cannot — do. https://t.co/tiiziqZ2PP
Fascinating new #QJPS from Baum, Cohen and Zhukov uses automated content analysis of US newspaper articles from 2000-13 to temporally and spatially measure rape culture, and suggests it predicts the incidence of rape itself @womenalsoknow https://t.co/s1kSooF2Te