**Financial Performance Data Table**This table provides key financial metrics across various records. The columns are defined as follows:- **ROAA (%)**: Return on Average Assets, a measure of a company's profitability relative to its total assets.- **Efficiency Ratio (%)**: Indicates the expenses as a percentage of revenue, used to gauge efficiency.- **Total Risk-Based Capital (%)**: A measure of a bank's capital, considering the riskiness of assets in its balance sheet.**Data:**| ROAA (%) | Efficiency Ratio (%) | Total Risk-Based Capital (%) ||----------|----------------------|------------------------------|| 1.04 | 39.93 | 17.04 || 0.68 | 57.75 | 13.88 || 7.27 | 81.4 | 27.77 || 1.08 | 53.49 | 18.31 || 0.72 | 71.08 | 14.66 || 0.92 | 65.41 | 14.04 || 0.79 | 68.07 | 13.38 || 1.04 | 68.14 | 16.8 || 1.76 | 68.1 | 16.69 || 1.07 | 64.82 | 13.86 || 1.37 | 48.58 | 12 || 0.93 | 63.1 | 18.65 || 0.66 | 59.16 | 19.76 || 1.72 | 49.93 | 17.69 || 1.5 | 54.7 | 26.6 || 0.59 | 81.6 | 15.08 || 2.12 | 75.21 | 14.55 || 1.11 | 69.82 | 17.5 || 1.45 | 49.47 | 16.03 || 1.06 | 57.09 | 14.62 **Regression Analysis of Bank Profitability**Profitability remains a challenge for banks and thrifts with less than $2 billion of assets. One of the critical business problems for bank analysts is understanding the factors that affect the return on average assets (ROAA), which indicates how profitable a company is relative to its total assets. In this scenario, data collected from a sample of 20 community banks resulted in the regression model:\[\hat{Y}_i = -4.511 + 0.037X_{1i} + 0.217X_{2i}\]where $Y$ is the ROAA (%), $X_1$ is the efficiency ratio (%), and $X_2$ is the total risk-based capital (%). ### ObjectiveComplete parts (a) through (d) below.- **a. Plot the Residuals versus $\hat{Y}_i$:**The task is to choose the correct graph that plots the residuals against the predicted values ($\hat{Y}_i$).### Graphs:Below are four potential graphs labeled A, B, C, and D, where the x-axis represents "Predicted Y" and the y-axis represents "Residuals."- **Graph A:** The residuals are mostly uniform across different predicted values, indicating a random distribution. - **Graph B:** Residuals appear to have a pattern, clustering in certain areas, suggesting possible issues with the regression model's assumptions. - **Graph C:** The residuals are scattered randomly without a discernible pattern, which is ideal for regression diagnostics. - **Graph D:** The residuals demonstrate a systematic pattern, which may indicate model issues.Choose the graph that best represents a random distribution of residuals, which typically indicates a well-fitting regression model.

Profitability remains a challenge for banks and thrifts with less than $2 billion of assets. The business problem facing a bank analyst relates to the factors that affect return on average assets (ROAA), an indicator of how profitable a company is relative to its total assets. Data collected from a sample of 20 community banks resulted in the regression model Y₁ = -4.511 +0.037X₁ +0.217X2, where Y is the ROAA (%), X₁ is the efficiency ratio (%), and X₂ is the total risk-based capital (%). Complete parts (a) through (d) below. Click the icon to view the table of data. a. Plot the residuals versus O A. Predicted Y Ŷ. Choose the correct graph below. Residuals B. H™ Predicted Y Residuals Predicted Y Q Residuals Predicted Y Q G

Profitability remains a challenge for banks and thrifts with less than $2 billion of assets. The business problem facing a bank analyst relates to the factors that affect return on average assets (ROAA), an indicator of how profitable a company is relative to its total assets. Data collected from a sample of 20 community banks resulted in the regression model Y₁ = -4.511 +0.037X₁ +0.217X2, where Y is the ROAA (%), X₁ is the efficiency ratio (%), and X₂ is the total risk-based capital (%). Complete parts (a) through (d) below. Click the icon to view the table of data. a. Plot the residuals versus O A. Predicted Y Ŷ. Choose the correct graph below. Residuals B. H™ Predicted Y Residuals Predicted Y Q Residuals Predicted Y Q G

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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