PART 1 – DATA ANALYSIS
Consider a manufacturing plant that produces high-quality products primarily using skilled labor. They are concerned about defects found in the surface coating for their product and have been provided a dataset
containing quality ratings for a sample of products. Note that each prompt below may require more than one visualization and/or analysis to fully answer.
1. Conduct an initial exploration of the data and summarize any key features. This must include, but is not limited to, 1) descriptive statistics, 2) features of the response variable, and 3) identifying any limitations of the dataset such as missing data or outliers.
Note that this evaluation should include some visual exploration of the data (i.e., histograms, box plots, scatter plots, etc.).
2. The current performance target is a quality rating of 85.0. Do the data suggest that they are
currently meeting this requirement?
3. Is there a significant difference in the average surface quality ratings for products produced on each of the two Production Lines?
4. Is the variation in surface quality consistent across the two Production Lines?
5. Observations showed that employees were using different methods to apply the surface coating.
Are there any significant differences in the resulting quality ratings from each of these methods?
6. They currently have four teams of employees with different levels of experience that affect the
quality of the products they produce. Is there evidence that there is a significant difference in the
average surface quality ratings for products produced on each of the two Production Lines when
controlling for the differences in teams?
7. What conditions (i.e., combinations of Line, Team, and Method) are associated with the best and
worst product quality ratings?
Answer these questions that addresses each of the prompts above in a separate sub-section. For each prompt, your report should 1) describe and justify your approach, 2) summarize the statistical results, 3) identify any potential limitations, and 4) discuss your conclusions, insights, and recommendations.
• The report must follow APA formatting requirements and may not exceed 10 pages
• The report should be in narrative form appropriate for reporting to a client or supervisor.
• Only include images (charts, graphs, tables) from your Minitab output as needed to support your narrative (your full statistical results should be documented in the Minitab Project file).
• For each test performed (hypothesis test, ANOVA model), the analysis must include verifying
relevant assumptions, conducting post hoc analysis, and evaluating statistical power of the test
when relevant.
• If a valid model cannot be created, then discuss the results under the condition that the model is known to be invalid and identify next steps for the analysis.
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