### Analyzing Helicopter Assembly Data for Learning Curve PhenomenonThe Helicopter Division of Aerospatiale is examining assembly costs at its Marseilles plant. Historical data show the relationship between the helicopter number and labor hours, suggesting a "learning curve" effect where labor hours decrease over time.#### ObjectiveConstruct a scatter plot and use Excel's Trendline feature to identify the best curvilinear trendline (not exceeding a second-order polynomial) that maximizes \( R^2 \).#### Data and AnalysisA table with the number of hours per helicopter is provided:| Helicopter Number | Labor Hours ||-------------------|-------------|| 1 | 2000 || 2 | 1400 || 3 | 1238 || 4 | 1142 || 5 | 1075 || 6 | 1029 || 7 | 965 || 8 | 957 |### Steps for Analysis1. **Data Visualization**: Construct a scatter plot based on the provided data to visually assess the trend. 2. **Residual Analysis**: Observe the residual plot, which exhibits a nonlinear pattern, suggesting that a linear model is unsuitable.3. **Model Selection**: Evaluate different trendline models to maximize \( R^2 \).#### Trendline Options- **Option A: Logarithmic** - \( R^2 \) value needed. - Equation: \( y = a \ln(x) + b \).- **Option B: Exponential** - \( R^2 \) value needed. - Equation: \( y = ae^{bx} \).- **Option C: Power** - \( R^2 \) value needed. - Equation: \( y = ax^b \).- **Option D: Polynomial (Second-order)** - \( R^2 \) value needed. - Equation: \( y = ax^2 + bx + c \).**Choose the best model** based on the highest \( R^2 \) value after rounding coefficients as specified.This analysis aids in understanding the reduction in labor hours, indicative of increased efficiency in helicopter production.

The R2 value helps us to identify the best fit of model for the data. The higher R2 value provides good fit model for the considered data. Construct the Scatter plot using Excel : Arrange the two variables of data in each column separately Select the entire data range (Example A1: B10) From the Insert tab go to recommended chart [ select the XY(scatter) from All charts] Draw an appropriate scatter plot Right click on the graph on any of the plotted points, and select the option add Trendline from the list. From trendline Options, select required non linear method , And tick on the boxes for Display Equation on chart, and Display R-squared on chart. (A) From the above Scatter plot, the R2 value is 0.927 The equation is, y = -470.9ln(x) + 1852.4 (B) From the above Scatter plot, the R2 value is 0.793 The equation is, y = 1787.4 e-0.1x C) From the above Scatter plot, the R2 value is 0.970 The equation is, y = 1875.9 x0.3 (D) From the above Scatter plot, the R2 value is 0.923 The equation is, y = 30.94x2 - 398.35x + 2231.8 Answer : The Power curve having the Maximum R2 value 0.970 out of the all models. Further, it explains that 97.0% of the data is good fit for Power curve model. Hence, Option (C) is correct