moments nextlet' talk about moments moments are fancy mathematical phrasebut you don' actually need math degree to understand itthough intuitivelyit' lot simpler than it sounds it' one of those examples where people in statistics and data science like to use big fancy terms to make themselves sound really smartbut the concepts are actually very easy to graspand that' the theme you're going to hear again and again in this book basicallymoments are ways to measure the shape of data distributionof probability density functionor of anythingreally mathematicallywe've got some really fancy notation to define themif you do know calculusit' actually not that complicated of concept we're taking the difference between each value from some value raised to the nth powerwhere is the moment number and integrating across the entire function from negative infinity to infinity but intuitivelyit' lot easier than calculus moments can be defined as quantitative measures of the shape of probability density function readyhere we go the first moment works out to just be the mean of the data that you're looking at that' it the first moment is the meanthe average it' that simple the second moment is the variance that' it the second moment of the dataset is the same thing as the variance value it might seem little bit creepy that these things kind of fall out of the math naturallybut think about it the variance is really based on the square of the differences from the meanso coming up with mathematical way of saying that variance is related to mean isn' really that much of stretchright it' just that simple