Background: False precision (also called overprecision, fake precision, misplaced precision and spurious precision) occurs when numerical data are presented in a manner that implies better precision than is justified; since precision is a limit to accuracy, this often leads to overconfidence in the accuracy, named precision bias.[1]

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Which data set most likely is not as precise as it looks, data set A or data set B?
Answer: data set A

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Which data set most likely is as precise as it looks, data set A or data set B?
Answer: data set B

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: If accuracy is of concern, which data set should he present to the lawmakers?
Answer: data set B

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: If accuracy is of concern, which data set should he not present to the lawmakers?
Answer: data set A

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Which data set most probably would cause precision bias, data set A or data set B?
Answer: data set A

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Which data set most probably would not cause precision bias, data set A or data set B?
Answer: data set B

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Would data set A cause overconfidence or no overconfidence in the accuracy?
Answer: overconfidence

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Would data set B cause overconfidence or no overconfidence in the accuracy?
Answer: no overconfidence

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Would lawmakers make better decisions or worse decisions with data set A when accuracy matters?
Answer: worse decisions

Situation: David has been working for the government for many years. His expertise is in statistics. He analyzes numerical data to help lawmakers make better decisions. He has now two sets of data in front of him, data set A and data set B. His evaluation finds that data set A is subject to false precision, but data set B is not subject to false precision. He has to decide which data set should be presented to the lawmakers.

Question: Would lawmakers make better decisions or worse decisions with data set B when accuracy matters?
Answer: better decisions