Continuous data measures things like temperature that can be any value. Discrete data counts things like how many people prefer chocolate ice cream! One flows, one hops π
Did you know that in 1900 only 4% of men were 6 feet or taller, but now it's 25%? Guess our ancestors were just trying to stay closer to the ground π
Check out the awesome, original artwork!
One bird flies left while the whole flock goes right - that's your classic outlier in action! Rebel bird is definitely not following the flock mentality! π¦π
SwiftStats StatsShort:
β Scatterplots = Show relationship between two variables visually
β Correlation = Measures strength of linear relationship (-1 to +1)
β Only catches linear patterns (misses curved, U-shaped relationships π)
Variance measures how spread out your data points are from the average! Think of it like measuring how messy your friend group is - low variance means you're all pretty similar, high variance means someone's always the weird one. Sorry, Jessica! π
SwiftStats StatsShort:
β Standard deviation = How spread out your data is from the mean
β Small SD = Data clustered together, Large SD = Data scattered
β Hard to interpret alone (what does "SD = 5.2" mean? π€·ββοΈ)
β Also sensitive to outliers (one extreme value inflates all)
Octopuses have 8 arms and 0 tentacles! Those wiggly things are actually arms with suckers all the way down - tentacles only have suckers at the tips. π
SwiftStats StatsShort:
β Box = Middle 50% of your data (Q1 to Q3)
β Line in box = Median, whiskers = data range, dots = outliers
β Looks simple but hides data shape (bimodal distributions look normal π)
β Can't see sample size (1000 vs 10 data points look identical)