Crazy Manufacturing

(One/Two Sample Hypothesis Test - mean & proportion)

Background

Crazy Manufacturing is producing plastic casings for packing smartphones. Its process engineer Martin Smith decides to perform quality control checks one of the casings ABC which occupies over 50% of their production. Doing so is because the number of customer complaints about ABCs quality is increasing by 40%. The increase in quality complaints mainly focus on the increasing dents on plastic casings and the under-size of the casings. Previous experience shows that the plastic casing, in general, has 5% defectives (population proportion of defectives). In addition, there is a requirement that ABC with length less than 10 inches will be regarded as defective. In summary, there are two issues Martin has to deal with:Testing the population proportion of defectives of ABC,Testing the population mean of ABCs lengthHas the quality of ABC been improved? (No matter your answer is Yes/No, please explain and provide evidence) 1. Develop a problem statement and establish the hypotheses for testing 2. Using minitab to measure & analyze to collect data and perform the necessary tests to understand the existing performance.

Step 1: A sample of 200 ABC was taken, and 20 of them were found defective.

• Choose StatBasic Statistics1 Proportion
  • Select Summarized data
  • Key in 20 for Number of events and 200 for Number of Trials
  • Click Perform hypothesis test and key in 0.05 for hypothesized proportion
  • Click Options. In the Options window
    • Set 95.0 as Confidence level
    • Select Proportion > hypothesized proportion as the Alternative hypothesis
    • Select Exact as the Method
    • Click OK
  • Click OK in the One-Sample Proportion window
• Determine if less than 5% population proportion defective rate is supported