Enter the population size, confidence level, and margin of error into the calculator to determine the required sample size for inventory auditing. This calculator helps in estimating the number of inventory items to sample when conducting an audit or quality control.

Inventory Sample Size Formula

The following formula is used to calculate the inventory sample size:

n = \frac{{(Z^2 \cdot p \cdot (1-p))}}{{e^2}} \cdot \frac{{1}}{{1 + (\frac{{(n - 1)}}{{N}})}}


  • N is the population size
  • Z is the Z-score associated with the desired confidence level
  • p is the estimated proportion of the attribute present in the population (typically 0.5 for maximum variability)
  • e is the margin of error

To calculate the inventory sample size, determine the Z-score for the desired confidence level, estimate the proportion of the attribute present in the population, and specify the margin of error. Then, apply the formula to find the sample size (n).

What is the Inventory Sample Size?

Inventory sample size is the number of items from a larger population of inventory that should be audited to estimate the characteristics of the whole inventory with a certain level of confidence. It is a crucial concept in inventory management, quality control, and statistical sampling.

How to Calculate Inventory Sample Size?

The following steps outline how to calculate the Inventory Sample Size.

  1. First, determine the population size (N) of the inventory.
  2. Next, determine the desired confidence level and find the corresponding Z-score (Z).
  3. Estimate the proportion of the attribute present in the population (p), often assumed to be 0.5 for maximum variability.
  4. Specify the margin of error (e) as a percentage.
  5. Apply the formula to calculate the sample size (n).
  6. After inserting the variables and calculating the result, check your answer with the calculator above.

Example Problem:

Use the following variables as an example problem to test your knowledge.

Population Size (N) = 1000 items

Confidence Level = 95%

Margin of Error (e) = 5%