If I had more values on the left side, this box would have been shifted over because a larger It's range goes fairly low to the left, but it might not haveĪ lot of value there. But for something like that, well something like that would have a tail to the left, would haveĪ tail to the left. It kind of looks something like that, and I can't draw because I'm doing this on the exercises right now. But a distribution that this could match up with is something that looks like having a tail down here, and then you kind of bump up here. Sure because we might have a whole bunch of 11s, not so much that it skews this, but we could have more than one. So if we were to try to visualize what this would look likeĪs maybe a histogram, and we don't know for Then the box defines the middle 50% of our numbers. Value of our data set, we have at least one 25. We have at least one 11, and then the maximum So just to remind ourselves, this tells us the minimum of our data set, the bottom of our range, so the minimum value in our data set. We're given a box and whiskers plot, which is really just telling us the different quartiles. Another way to thinkĪbout skewed to the left is that your mean is to the left of your median and mode. Process version of them are when you're left tailed, you also tend to be skewed to the left, and when you are right-tailed, you tend to be skewed to the right. Technical definitions when you get further in statistics, but a, I guess, easier to These other words mean, skewed to the left, or So I feel good about saying it is approximately symmetrical. Not exactly, this bucketĭoesn't quite match up to this one, but it's pretty close. If I were to draw a line of symmetry right down here, rightĪt around an age of, you know, the line would be right at an age of 65, I guess you could say all this is a bucket for ages 60 to 70, then you could flip it over and it looks pretty symmetrical. So we have a lot of guests that are between 60 and 70 years old, or reasonable that are between 50 and 60, or 70 or 80, and this distribution actually looks pretty symmetrical.

So this is the number of guests at Logan Assisted Living. They're saying by age, they're telling us the number of guests. Well yeah, these names aren't that great, but let's actually see

That because if you were to say, hey, maybe there'sĪ line of symmetry here and you tried to fold this over, it wouldn't match up, the two sides would not match up. You could fold over the line of symmetry, and they'll roughly meet. Is one where both sides of that line of symmetry are mirror images of each other. Remember symmetry, youĭefine a line of symmetry, and one type of symmetry Left-tailed and right-tailed, you're likely to beĪpproximately symmetrical. Left-tailed we would seeĪ tail going like that. To see a lot of examples, and frankly, you should too because it'll help you test your knowledge. I'm using Khan Academy exercises because it's a good way

So I'd call thisĭistribution right-tailed. But here when we have a few people between 60 and 70, evenįewer between 70 and 80, even fewer between 80 and 90, and you know, if it just kind of keeps going like this, this is a tail and it's on the right side, it's a right-tailed distribution. So this distribution right over here, it looks like it has a tail to the right. We actually use those types of words to describe distributions. If you were to imagine this were an armadillo, this would be the body of the armadillo, and then what we see to the right kind of looks like the So just when you lookĪt something like this, a distribution like this, something might pop out at you. Have a reasonable number between 20 and 30, we have a lot of guests at 30, in that bucket between 30 and 40, reasonable number between 40 and 50, and then as we get older, we have fewer and fewer guests. So we don't have any guests that are under the age of 20, we In each bucket, it tells us the number of guests that are in that age bucket. So right over here, let's see, we're talking about Matt's Cafe, and we have different age buckets, so this is a histogram here. Want to talk about now are shapes of distributionsĪnd different words we might use to describe those shapes.

Negative squeed histogram