Use to produce an interval estimated to contain a specified proportion of a population.
Tolerance Interval for Proportion (Normal Distribution)
- From an open JMP data table, select Analyze > Distribution.
- Select one or more continuous variables from Select Columns, click Y, Columns (continuous variables have blue triangles), and click OK.
- From the Distributions report window, select Tolerance Interval under the red triangle next to the variable name.
- Select the confidence level and specify proportion of the population you desire the interval to cover. Choose Two-sided or one-sided interval. Here we chose 95% confidence, 90% proportion to cover, and two sided.
- Choose to Assume Normal Distribution if you believe that is an appropriate model to use to describe the distribution of the variable for the population. Click OK.
Note: A goodness-of-fit test (not shown) indicates that a normal distribution is appropriate.
JMP will add a table displaying the lower and upper bound of the Tolerance Interval based upon assumption of a normal distribution.
Interpretation:
It is estimated, with 95% confidence, that 90% of pins produced by this process that these data can be considered a sample from will have a Weight between 17.3 and 23.5.
Tolerance Interval for Proportion (Non-Normal Distribution)
- Follow steps 1-3 above.
- In the Tolerance Interval Dialog box, choose Nonparametric method. Click OK.
Note: A goodness-of-fit test (not shown) indicates that a normal distribution is not an appropriate model to use.
JMP will add a table displaying the lower and upper bound of the Tolerance Interval for any continuous distribution.
Note: The actual confidence level achieved may be larger than the value specified. Here it’s 97.6% confidence.
Interpretation:
It is estimated, with 97.6% confidence, that 90% of this process that these data can be considered a sample from have values between 5.23 and 17.2.
Visit Basic Analysis > Distributions > Options for Continuous Variables > Tolerance Intervals in JMP Help to learn more.