Acceptance Sample Size Calculator

Calculate Acceptance Sample Size (S)



Formula

The formula to calculate the Acceptance Sample Size (S) is:

\[ \text{S} = \frac{L \times A}{100} \]

Where:

Definition

Example

Let's say the lot size (L) is 1000 units and the acceptance number (A) is 5. Using the formula:

\[ \text{S} = \frac{1000 \times 5}{100} = 50 \]

So, the acceptance sample size (S) is 50 units.

Extended information about "Acceptance-Sample-Size-Calculator"

Sample Size Calculator Average

Definition: A sample size calculator helps determine the number of observations or replicates needed to achieve a desired level of accuracy.

Formula: \( n = \frac{Z^2 \cdot p \cdot (1 - p)}{E^2} \)

Example: \( n = \frac{1.96^2 \cdot 0.5 \cdot (1 - 0.5)}{0.05^2} \)

Acceptance Number in Sampling

Definition: The acceptance number in sampling is the maximum number of defective items allowed in a sample for the lot to be accepted.

Formula: \( c = \text{Maximum number of defects allowed} \)

Example: If the acceptance number is 2, then up to 2 defective items are allowed in the sample for the lot to be accepted.

Approximate Sample Size Calculator

Definition: An approximate sample size calculator estimates the number of samples needed based on desired confidence level and margin of error.

Formula: \( n = \frac{Z^2 \cdot p \cdot (1 - p)}{E^2} \)

Example: \( n = \frac{1.96^2 \cdot 0.4 \cdot (1 - 0.4)}{0.06^2} \)

Lot Acceptance Testing Sample Size

Definition: Lot acceptance testing determines the sample size needed to decide whether to accept or reject a lot based on the number of defects found.

Formula: \( n = \frac{N \cdot p}{A} \)

Example: \( n = \frac{1000 \cdot 0.02}{2} \)

Calculation for Sample Size

Definition: Calculating sample size involves determining the number of observations needed to achieve a desired level of accuracy and confidence.

Formula: \( n = \frac{Z^2 \cdot p \cdot (1 - p)}{E^2} \)

Example: \( n = \frac{1.96^2 \cdot 0.3 \cdot (1 - 0.3)}{0.04^2} \)

How to Estimate Sample Size

Definition: Estimating sample size involves calculating the number of observations needed to achieve a desired level of accuracy and confidence.

Formula: \( n = \frac{Z^2 \cdot p \cdot (1 - p)}{E^2} \)

Example: \( n = \frac{1.96^2 \cdot 0.25 \cdot (1 - 0.25)}{0.05^2} \)