**Transcription for Educational Website**---**Title: Analysis of Defective Parts Production****Section 1: Data Overview**- **Problem Statement:** - Defective parts produced by machine 1 and machine 2 using manual and automatic loading of parts are shown in the table below.- **Data Table:**| Machine | Loading Type | | ||--------------|--------------------|----------|----------|| | Manual Loading (ML)| | Auto Loading (AL) || | Trial 1 | Trial 2 | Trial 1 | Trial 2 || Machine 1 (M1)| 30 | 35 | 28 | 33 || Machine 2 (M2)| 18 | 24 | 21 | 25 |**Section 2: Calculations Required**A. Calculate the following averages: - \( \bar{Y}_{M1\cdot} \) - \( \bar{Y}_{M2\cdot} \) - \( \bar{Y}_{ML\cdot} \) - \( \bar{Y}_{AL\cdot} \) - \( \bar{Y}_{\cdot\cdot} \)B. Use the provided Analysis of Variance (ANOVA) table: 1. Fill in the degrees of freedom for machine, loading, and machine-loading interaction. 2. Calculate the F values for each source of variation. 3. Determine the p-values for each source. 4. Analyze which factors significantly affect the number of defectives.**Section 3: Analysis of Variance Table**| Source | DF | SS | MS | F-Value | P-Value ||-----------------|-----|--------|--------|---------|---------|| Machine | | 180.500| 180.500| | || Loading | | 8.000 | 8.000 | | || Machine*Loading | | | | | || Error | | 51.000 | 12.750 | | || Total | | 239.500| | | |**Section 4: Questions to Explore**C. Which factors have a significant

Given the defective parts produced by machine 1 and machine 2 using manual and automatic loading of…

Answered: 2. Defective parts produced by machine…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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/Skip/1 A beverage company has two bottling plants in different parts of the world. To insure uniformity in their product, the variances of the weights of the bottles at the two plants should be equal. But Stephanie, the company's vice president of quality assurance, suspects that the variance at bottling plant A is more than the variance at bottling plant B. To test her suspicions, Stephanie samples 37 bottles from bottling plant A and 33 bottles from bottling plant B, with the following results (in ounces): Bottling Plant A: 12.4, 12.4, 13.4, 14.3, 12.7, 12.7, 13.7, 12.4, 12.8, 12.4, 12.9, 12.7, 12.8, 13.3, 13.8, 12.7, 12.4, 11.9, 12.9, 13, 13.1, 12.4, 12.7, 12.6, 12.5, 13.3, 12.2, 13.3, 12.8, 12.7, 13.2, 13.1, 11.7, 13, 12.3, 13.1, 12.4 Bottling Plant B: 12.9, 12, 13.4, 12.4, 12.4, 12.9, 12.7, 12.1, 11.4, 13.1, 14.1, 12.5, 12.7, 11.5, 12.3, 12.7, 13.7, 12.6, 13.9, 12.7, 12, 12.5, 11.7, 13.6, 11.4, 13.6, 14, 12, 11.5, 12, 11.7, 13, 11.8 Perform a hypothesis test using a 3% level of…

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