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Hypothesis Testing & Confidence Interval

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Please see the attached problem.

A manufacturing company produces water filters for home refrigerators. The process has typically produced about 4% defective. A recently designed experiment has led to changing the seal to reduce defects. With the process running using the new seal, a random sample of 300 filters yielded 7 defects.

a. Conduct the most appropriate hypothesis test using a 0.10 significance level.
b. Construct a 90% confidence interval for the true proportion of defective water filters.

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Solution Summary

The following solution provides a step by step method for the calculations required to test hypotheses and confidence intervals for population proportions. Formulas for the calculation and interpretations of the results are also included. An interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.

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a. Here we need to test whether the defective filters reduced with the seal change. Hence lower tailed z-test for proportion is most appropriate.
The null hypothesis tested is
H0: The proportion of defective water filters after the seal change ≥ 0.04. (p≥0.04)
The alternative hypothesis is
H1: The proportion of defective water filters after the seal change < 0.04. (p<0.04)
The test statistic used is

Rejection criteria: ...

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