Am I the only one who feels like:

(E): more adolescents thieves --> on avg. less experienced thieves --> more likely to get caught --> more likely to get convicted

Is the same number and just as (un)reasonable of assumptions as:

less likely to abandon b4 noticed --> on avg. more time in noticed stolen cars --> more likely to get caught --> more likely to get convicted

I still chose (A) bc it seemed like the whole ans. was more relevant to the whole stim. but doing blind review I got more confused lol. Feels like (E) isn't as "terrible" as they're saying

#feedback #help

Am I wrong to think that the written analysis by AlexandraNash maps out different suff./necess. conditions than JY's video?

She says Lucy "poses an alternative necessary condition: having a unique methodology" whereas JY's video says "unique methodology" is a sufficient condition. Am I misunderstanding or are these in disagreement?

JY analysis: UniqMeth --> AutoDisc

AN analysis: AutoDisc --> UniqMeth

I believe JY's analysis is correct was just a little confused.

Like in this question, if it seems very very likely based on solid understanding of the stimulus that A is correct, should we always move on without any POE on other answer choices (under timed conditions). Or could it / would it be advisable to do a quick skimming POE regardless (again just talking about under timed conditions)?

#feedback Under heading Answer Choice B it has "fees for viewers" which should be "fees from viewers"

#feedback Would there be a way to choose a timed format for the You Try or Adaptive Drill, where we are either told a set amount of time we have to begin with or the ideal time per question beforehand?

Sometimes find myself either going way too slowly or flying through questions blindly trying to mimic test conditions or not. It could be a good way to start being more conscious of timing for newbies!

Lol, totally understand the main point in the blinding section, but to say the data scientists should be blinded is kind of hilarious.

If the doctors were blinded who collected the data, and the data scientists who are analyzing it are as well, who's going to analyze the data? Does anyone know who's who? What are we even doing?!?! Ahhh they blinded me too!!!!!!!

Again I understand what they were meaning to say (don't bias the data collectors to compromise the data) but coming from a data science background just a funny idea.

#feedback Am I the only one who noticed that the video did not include Group 1 Inidcator 7 "the only"? Took notes off the video instead of the written explanation and later proceeded to miss a question in the exercises from this mistake. Oops!

As a pneumonic for this strategy I like WWW.

1. What? - What is being compared

2. What on? - What quality are they being compared on?

3. Winner? - Who's the winner?