Don't Just Say "You're Wrong." Tell What's *RIGHT*

[Measure_for_Measure]

I googled my screen name and the word “um” for this message board. Here is the wall of shame or imprudence. I will bold the word um where needed.

@Measure_for_Measure

…
Space cup. They have a working prototype in the International Space Station. Now they want to make them out of glass for zero g and 1 g encounters.

Q1) Um, why? I know 3-D laser printing is expensive, but c’mon.
My guess: because it’s cool for earthbound folk. Eh, ok.
Q2) That base looks a little narrow for 1 g environments.

The group also says, “With this project supported we’ll also have resources to invest in more like-minded living-and-working in space demonstrations. We’ll let you know what we mean soon…” That I can get behind. I’m pretty excited about working out nuts and bolts stuff.
https://www.kickstarter.com/projects/spaceware/space-coffee-cup

That wasn’t directed against a poster, but rather at a kickstarter project. Probably ok (???)

@Duck_Duck_Goose

Um, beg to differ. Has not “been invented”. Is “in the process of being researched” if he ever gets any funding. Notice the words “could offer”, “could allow”, “could begin”, and “could be”.
We now return you to your regularly scheduled debate on The Ethics of the Orgasmatron.

That seems ok to me, and way not ok to others. Or so I guess.

@Ourrah

Um, wow.

Not helpful, but mainly due to vagueness.
Ok, here’s where I apparently messed up due to cluelessness. I’ll present the exchange.

@Achernar

In my intro Psychology text, it said that for what it was designed for, this test had a correlation coefficient of 0.33, which means that if you wanted to find the answer to a yes-no question, you’d get it right about 66% of the time. Of course, flipping a coin gets you the right answer 50% of the time. You wouldn’t want to say that it’s absolutely useless, but if you were trying to determine something, you’d probably use more than just this test.

I think I should point out that, IMO, there are a few things in Psychology that the average person believes would be absolutely useless, but that have been shown through scientific studies not to be.

@Measure_for_Measure

Achernar: Um, I believe you’re thinking about the coefficient of determination (R2) which is the square of the correlation coefficient.

In your example a correlation coefficient of .33 implies that one variable can explain about 11% of the variance.

.33^2=.11
Not sqrt(.33) (=.57)

FWIW, .33 might indicate a moderate effect, except that I’m not sure what variables are being studied here.

@Achernar

Okay, my apologies for getting that wrong. I don’t remember that certainly the measurement that was given in the book, but I’m fairly sure about the 66% figure.

I certainly did not think Achernar was an idiot and am fully capable of making a similar mistake. It’s easy to do. I was trying to be conversational and even polite. I suppose I may have wanted a “Wake up” word of some sort, but there was absolutely nothing dumb about what I was responding to.

Proposed expression: “Just to clarify”. Then add softener at the end. I dunno.