# Accuracy and Precision

They mean slightly different things!

## Accuracy

Accuracy is how close a measured value is to the actual (true) value.

## Precision

Precision is how close the measured values are to each other.

## Examples

### And an example on a Target:

 High Accuracy Low Precision Low AccuracyHigh Precision High AccuracyHigh Precision

### Example: Hitting the Post

If you are playing football and you always hit the right goal post instead of scoring, then you are not accurate, but you are precise!

## How to Remember?

• aCcurate is Correct (a bullseye).
• pRecise is Repeating (hitting the same spot, but maybe not the correct spot)

## Bias (don't let precision fool you!)

When we measure something several times and all values are close, they may all be wrong if there is a "Bias"

Bias is a systematic (built-in) error which makes all measurements wrong by a certain amount.

### Examples of Bias

• The scales read "1 kg" when there is nothing on them
• You always measure your height wearing shoes with thick soles.
• A stopwatch that takes half a second to stop when clicked

In each case all measurements are wrong by the same amount. That is bias.

## Degree of Accuracy

Degree of Accuracy depends on the instrument we are measuring with. But as a general rule:

The Degree of Accuracy is half a unit each side of the unit of measure.

### Examples:

 When an instrument measures in "1"s any value between 6½ and 7½ is measured as "7" When an instrument measures in "2"s any value between 7 and 9 is measured as "8"

(Notice that the arrow points to the same spot, but the measured values are different!
Read more at Errors in Measurement. )

We should show final values that match the accuracy of our least accurate value used.

### Example: We are told the dog is about 2 feet high.

We can convert that to 609.6 mm, but that suggests we know the height to within 0.1 mm!

So we should use 600 mm