yego.me
💡 Stop wasting time. Read Youtube instead of watch. Download Chrome Extension

Examples thinking about power in significance tests | AP Statistics | Khan Academy


3m read
·Nov 11, 2024

A significance test is going to be performed using a significance level of five hundredths. Suppose that the null hypothesis is actually false. If the significance level was lowered to 100, which of the following would be true?

So pause this video and see if you can answer it on your own.

Okay, now let's do this together and let's see. They're talking about how the probability of a type 2 error or the power would change. So before I even look at the choices, let's think about this.

We've talked about in previous videos that if we increase our level of significance, that will increase our power and power is the probability of not making a type 2 error. So that would decrease the probability of making a type 2 error. But in this question, we're going the other way. We're decreasing the level of significance, which would lower the probability of making a type 1 error but this would decrease the power. It actually would increase the probability of making a type 2 error.

And so which of these choices are consistent with that? Well, choice A says that both the type two error and the power would decrease. Well, those don't… these two things don't move together. If one increases, the other decreases, so we rule that one out. Choice B also has these two things moving together, which can't be true. If one increases, the other decreases.

Choice C: the probability of a type II error would increase. That's consistent with what we have here and the power of the test would decrease. Yep, that's consistent with what we have here, so that looks good.

And choice D is the opposite of that; the probability of a type 2 error would decrease. So this is— they're talking about this scenario over here and that would have happened if they increased our significance level, not decreased it. So we could rule that one out as well.

Let's do another example. Asha owns a car wash and is trying to decide whether or not to purchase a vending machine so that customers can buy coffee while they wait. She'll get the machine if she's convinced that more than 30 percent of her customers would buy coffee.

She plans on taking a random sample of n customers and asking them whether or not they would buy coffee from the machine and she'll then do a significance test using alpha equals 0.05 to see if the sample proportion who say yes is significantly greater than 30 percent.

Which situation below would result in the highest power for her test? So again pause this video and try to answer it.

Well, before I even look at the choices, we can think about what her hypotheses would be. Her null hypothesis is—you could kind of view it as a status quo, no news here—and that would be that the true population proportion of people who want to buy coffee is 30 percent.

And that her alternative hypothesis is that no, the true population proportion, the true population parameter there is greater than 30 percent.

And so if we're talking about what would result in the highest power for her test—so a high power means the lowest probability of making a type 2 error. In other videos we've talked about, it looks like she's dealing with the sample size and what is the true proportion of customers that would buy coffee.

And the sample size is under her control; the true proportion isn't. Don't want to make it seem like somehow you can change the true proportion in order to get a higher power. You can change the sample size but the general principle is: the higher the sample size, the higher the power.

So you want the highest possible sample size and you're going to have a higher power if the true proportion is further from your hypothesis—your null hypothesis proportion. And so we want the highest possible n and that looks like an n of 200, which is there and there.

And we want a true proportion of customers that would actually buy coffee as far away as possible from our null hypothesis which once again would not be under Asha's control. But you can clearly see that 50 is further from 30 than 32 is. So this one, choice D, is the one that looks good.

More Articles

View All
The Spirit of Takumi | National Geographic
[Music] While I was in Hiroshima, Japan, I met craftsmen who embodied the Japanese tradition of takumi. Takumi means, in Japanese, a master craftsman, but it is so much more than that. It’s not just a job; it’s a passion; it’s a total dedication to a sing…
Being Unhappy Is Very Inefficient
Besides, I’m too smart for it. The other objection is I don’t want it to lower my productivity. I don’t want to have less desire or less work ethic. Fact-check, and that is true. The more happy you are, the more content and peaceful you are. That’s less l…
How Big Can a Person Get?
Hey, Vsauce. Michael here. Ten centimeters - about four inches. This is how much taller on average people are today than they were 150 years ago. Better nutrition and medical care early in life has allowed us to better take advantage of the blueprints wi…
You're not boring : How to awaken your creativity
When it comes to creativity, for some reason, most people take creativity as something that you’re born with, as something like a talent. Most of us think either we haven’t or we don’t. But in reality, creativity is something that you’ve worked for and th…
I Fed a Chameleon From My Mouth To Study Its Mouth ( In Slow Motion) | Smarter Every Day 180
Hey, it’s me Destin, welcome back to Smarter Every Day. I’ve been wanting to do this video forever. Chameleons’ tongues are very unique, and this is a very hungry chameleon right now, and I’m going to see if I can feed him by holding a cricket in my mouth…
Making Something Social Destroys the Truth of It
Making something social destroys the truth of it because social groups need consensus to survive. Otherwise, they fight; they can’t get along. Consensus is all about compromise, not about truth-seeking. Science was this unique discipline, at least in Natu…