MBS659 - Predicting Audit Fees A Multivariate Analysis Assignment

Assignment Task

Objective

The objective of this assignment is to utilize various analysis techniques to predict audit fees based on various financial and non-financial factors such as market capitalization, industry, auditor, balance sheet assets, beta, and sales.

Dataset

Use a dataset containing information on audit fees, market capitalization, industry classification, auditor details, balance sheet assets, beta values, and sales for a sample of companies. See details of variables in the appendix.

Tasks

1. Data Exploration

• Provide a summary of the dataset, including descriptive statistics, missing values, and outliers. 
• Visualize the relationships between audit fees and each predictor variable using scatter plots.

2. Correlation Analysis:

• Calculate and interpret the correlation matrix between audit fees and predictor variables.
• Identify the variables with the highest and lowest correlations with audit fees.

3. Regression Analysis:

• Perform a multiple linear regression analysis with audit fees as the dependent variable and all predictor variables as independent variables.
• Evaluate the overall fit of the regression model using appropriate statistics (R-squared, F-statistic).
• Interpret the regression model coefficients, paying particular attention to the significance levels.

4. Factor Analysis:

• Conduct a factor analysis to identify latent factors that explain the shared variance among the predictor variables.
• Examine the factor loadings and determine the interpretation of each factor.
• Assess whether the identified factors provide insights into the underlying structure of the data and the potential for dimensionality reductio
• Compare the predicted and actual audit fees to assess the model's accuracy.

5. Other Analysis:

• Robust
• Sensitivity

6. Discussion and Conclusion:

• Summarize the key findings from the regression, correlation, and factor analyses.
• Discuss the variables that significantly influence audit fees and their respective magnitudes.
• Reflect on the limitations of the analysis and potential areas for further research

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