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The Helicopter Division of Aerospatiale is studying assembly costs at its Marseilles plant. Past data indicates the accompanying data of number of labor hours per helicopter. Reduction in labor hours over time is often called a "learning curve" phenomenon. Using these data, apply simple linear regression and examine the residual plot. What do you conclude? Construct a scatter chart and use the Excel Trendline feature to identify the best type of curvilinear trendline (but not going beyond a second-order polynomial) that maximizes R. E Click the icon to view the Helicopter Data. The residuals plot has a nonlinear shape. Therefore, this data cannot be modeled with a linear model Determine the best curvilinear trendline that maximizes R. Data table for number of hours per helicopter OA. The best trendline is Logarithmic with an R? value of The equation is y = O In (x) (Round the coefficient of the logarithm to one decimal place as needed. Round all other values to three decimal places as needed.) O B. The best trendline is Power with an R value of The equation is y= Dx. (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) OC. The best trendline is Polynomial with an R value of The equation is y Ox+x+ TT Helicopter Number Labor Hours 2000 1500 1237 1145 1071 3 4 (Round to three decimal places as needed.) 6. 1028 984 OD. The best trendline is Exponential with an R? value of The equation is y = ()e. 955 (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) Print Done

The Helicopter Division of Aerospatiale is studying assembly costs at its Marseilles plant. Past data indicates the accompanying data of number of labor hours per helicopter. Reduction in labor hours over time is often called a "learning curve" phenomenon. Using these data, apply simple linear regression and examine the residual plot. What do you conclude? Construct a scatter chart and use the Excel Trendline feature to identify the best type of curvilinear trendline (but not going beyond a second-order polynomial) that maximizes R. E Click the icon to view the Helicopter Data. The residuals plot has a nonlinear shape. Therefore, this data cannot be modeled with a linear model Determine the best curvilinear trendline that maximizes R. Data table for number of hours per helicopter OA. The best trendline is Logarithmic with an R? value of The equation is y = O In (x) (Round the coefficient of the logarithm to one decimal place as needed. Round all other values to three decimal places as needed.) O B. The best trendline is Power with an R value of The equation is y= Dx. (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) OC. The best trendline is Polynomial with an R value of The equation is y Ox+x+ TT Helicopter Number Labor Hours 2000 1500 1237 1145 1071 3 4 (Round to three decimal places as needed.) 6. 1028 984 OD. The best trendline is Exponential with an R? value of The equation is y = ()e. 955 (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) Print Done

MATLAB: An Introduction with Applications
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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### Analysis of Assembly Costs in Helicopter Division at Marseilles Plant The Helicopter Division of Aerospatiale is examining the assembly costs at its Marseilles plant. An analysis of labor hours per helicopter has been conducted, reflecting a "learning curve" phenomenon over time. The objective is to use this data to apply curvilinear regression analysis for modeling and trend identification. **Key Observation:** - The residuals plot exhibits a nonlinear pattern, indicating that a linear model is inappropriate for this data set. **Objective:** - Determine the best curvilinear trendline that maximizes \( R^2 \), a statistic that measures the proportion of variability captured by the model. ### Data Table A table lists the helicopter number and corresponding labor hours: | Helicopter Number | Labor Hours | |-------------------|-------------| | 2 | 2000 | | 3 | 1500 | | 4 | 1237 | | 5 | 1145 | | 6 | 1071 | | 7 | 1028 | | 8 | 984 | | 9 | 955 | ### Trendline Options 1. **Logarithmic Trendline** - Equation: \( y = (\text{Coefficient}) \ln(x) + \text{Constant} \) - Requires rounding the coefficient of the logarithm to one decimal place and other values to three decimal places. 2. **Power Trendline** - Equation: \( y = (\text{Coefficient}) x^{\text{Exponent}} \) - Requires rounding the coefficient to one decimal place and other values to three decimal places. 3. **Polynomial Trendline (up to second-order)** - Equation: \( y = (\text{Coefficient}) x^2 + \text{Coefficient} x + \text{Constant} \) - The first coefficient should be rounded to one decimal place, other values to three decimal places. 4. **Exponential Trendline** - Equation: \( y = (\text{Coefficient}) e^{\text{Exponent} x} \) - Requires rounding the coefficient and exponent to one decimal place, other values to three decimal places. ### Conclusion Through constructing a scatter chart and utilizing Excel's Trendline feature, identify the optimal type of curvilinear trendline from the options listed above, ensuring it
Transcribed Image Text:### Analysis of Assembly Costs in Helicopter Division at Marseilles Plant The Helicopter Division of Aerospatiale is examining the assembly costs at its Marseilles plant. An analysis of labor hours per helicopter has been conducted, reflecting a "learning curve" phenomenon over time. The objective is to use this data to apply curvilinear regression analysis for modeling and trend identification. **Key Observation:** - The residuals plot exhibits a nonlinear pattern, indicating that a linear model is inappropriate for this data set. **Objective:** - Determine the best curvilinear trendline that maximizes \( R^2 \), a statistic that measures the proportion of variability captured by the model. ### Data Table A table lists the helicopter number and corresponding labor hours: | Helicopter Number | Labor Hours | |-------------------|-------------| | 2 | 2000 | | 3 | 1500 | | 4 | 1237 | | 5 | 1145 | | 6 | 1071 | | 7 | 1028 | | 8 | 984 | | 9 | 955 | ### Trendline Options 1. **Logarithmic Trendline** - Equation: \( y = (\text{Coefficient}) \ln(x) + \text{Constant} \) - Requires rounding the coefficient of the logarithm to one decimal place and other values to three decimal places. 2. **Power Trendline** - Equation: \( y = (\text{Coefficient}) x^{\text{Exponent}} \) - Requires rounding the coefficient to one decimal place and other values to three decimal places. 3. **Polynomial Trendline (up to second-order)** - Equation: \( y = (\text{Coefficient}) x^2 + \text{Coefficient} x + \text{Constant} \) - The first coefficient should be rounded to one decimal place, other values to three decimal places. 4. **Exponential Trendline** - Equation: \( y = (\text{Coefficient}) e^{\text{Exponent} x} \) - Requires rounding the coefficient and exponent to one decimal place, other values to three decimal places. ### Conclusion Through constructing a scatter chart and utilizing Excel's Trendline feature, identify the optimal type of curvilinear trendline from the options listed above, ensuring it
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