Moving average model
A moving average model is like the average you calculate in math class, but it's used in statistics.
Imagine you have a box of colored pencils, and you want to know what the most popular color is. You ask your friends to choose their favorite color from the box and write it down. The first friend says "red," the second friend says "blue," and the third friend says "green." To find the average color, you would add up all the colors and divide by the number of friends. So you would have (red + blue + green) / 3 = (1 + 1 + 1) / 3 = 1.
Now imagine you have a graph with some data points. Maybe it shows how many cookies you eat each day for a week. On Monday, you ate 10 cookies. On Tuesday, you ate 12 cookies. On Wednesday, you ate 8 cookies. On Thursday, you ate 14 cookies. On Friday, you ate 16 cookies. On Saturday, you ate 18 cookies. On Sunday, you ate 9 cookies.
If you wanted to know the average number of cookies you ate each day, you could use the same formula as before: add up all the numbers and divide by the number of days. So you would have (10+12+8+14+16+18+9) /7 = 77/7 = 11.
But what if you just wanted to know the average from the last three days? That's where the moving average model comes in. You "move" your group of data points over to the right to look at a smaller set of numbers. So instead of looking at all seven days, you only consider the last three.
If you do that, you would have (16+18+9) / 3 = 43/3 = 14.33. So the moving average for the last three days is 14.33 cookies.
You can use a moving average model to look at different time periods, like the last five days, or the last ten days, or any number of days you want. It's a way to see how a trend is changing over time without getting too overwhelmed by too much data.
Imagine you have a box of colored pencils, and you want to know what the most popular color is. You ask your friends to choose their favorite color from the box and write it down. The first friend says "red," the second friend says "blue," and the third friend says "green." To find the average color, you would add up all the colors and divide by the number of friends. So you would have (red + blue + green) / 3 = (1 + 1 + 1) / 3 = 1.
Now imagine you have a graph with some data points. Maybe it shows how many cookies you eat each day for a week. On Monday, you ate 10 cookies. On Tuesday, you ate 12 cookies. On Wednesday, you ate 8 cookies. On Thursday, you ate 14 cookies. On Friday, you ate 16 cookies. On Saturday, you ate 18 cookies. On Sunday, you ate 9 cookies.
If you wanted to know the average number of cookies you ate each day, you could use the same formula as before: add up all the numbers and divide by the number of days. So you would have (10+12+8+14+16+18+9) /7 = 77/7 = 11.
But what if you just wanted to know the average from the last three days? That's where the moving average model comes in. You "move" your group of data points over to the right to look at a smaller set of numbers. So instead of looking at all seven days, you only consider the last three.
If you do that, you would have (16+18+9) / 3 = 43/3 = 14.33. So the moving average for the last three days is 14.33 cookies.
You can use a moving average model to look at different time periods, like the last five days, or the last ten days, or any number of days you want. It's a way to see how a trend is changing over time without getting too overwhelmed by too much data.
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