A moving average is like taking a bunch of numbers and making them smoother so you can see the bigger picture more clearly.
Imagine you're on a playground swing. Every time you go up, it's like a high number, and every time you come down, it's like a low number. If you just look at each swing separately, it might seem like you’re going all over the place. But if you take an average of your swings, say, the last five, you can see how you're generally moving up or down overall. That’s what a moving average does with numbers: it helps you see trends more easily by averaging them out as they come in.
How It Works
A moving average looks at a set number of recent values and finds their average. Then, when the next value comes in, it drops off the old one and adds the new one, kind of like shifting a window forward on a line of numbers. This helps you see if things are going up or down over time without getting distracted by every little change.
Think of it like watching your favorite cartoon, sometimes there are quick cuts between scenes, but the moving average is like taking a slow-motion look at how the story is unfolding overall.
Examples
- A child tracks the number of candies they eat each day and uses a moving average to see if their candy intake is increasing or decreasing overall.
- A baker looks at the average number of loaves sold over the past week to decide how many to bake tomorrow.
Ask a question
See also
- What are non-uniform datasets?
- How Does Stem and Leaf Plots Work?
- What are nonparametric and semiparametric models?
- What are statistical populations?
- What are statistical inference models?