ASC454 Actuarial Programming UITM Assignment Answer Malaysia 

ASC454 Actuarial Programming is a course offered at UITM (Universiti Teknologi MARA) in Malaysia. This course focuses on teaching students the essential skills of using spreadsheet tools, particularly Microsoft Excel, and programming with Visual Basic Application (VBA) to solve actuarial problems. The Actuarial Programming course highlights the significance of comprehending the underlying principles of problems and approaching them systematically by leveraging Microsoft Excel and VBA. Actuarial problems covered in this course encompass Actuarial Mathematics, Financial Mathematics, Statistics, and other related areas.

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Assignment Task 1 : Demonstrate the technical skills in the actuarial related softwares.

In order to demonstrate technical skills in actuarial-related software, you can showcase your proficiency in the following commonly used software tools:

• Excel: Excel is a versatile tool widely used in actuarial work. You can demonstrate your skills in data manipulation, modeling, and analysis by performing tasks such as data cleaning, creating complex formulas, utilizing pivot tables, and generating charts and graphs.
• R: R is a programming language commonly used for statistical analysis and data visualization. You can demonstrate your skills by writing R scripts to perform actuarial calculations, fitting statistical models, simulating scenarios, and creating visual representations of data.
• Python: Python is another popular programming language used in actuarial work. You can showcase your skills by writing Python scripts to perform tasks such as data cleaning, statistical analysis, building predictive models, and automating repetitive processes.
• SAS: SAS (Statistical Analysis System) is a software suite widely used in the actuarial field. You can demonstrate your skills by performing tasks such as data management, statistical analysis, regression modeling, and generating reports using SAS programming.
• SQL: SQL (Structured Query Language) is essential for working with databases. You can showcase your skills by writing SQL queries to extract and manipulate data from databases, perform calculations, and create customized reports.

Assignment Task 2 : Develop and Use the decision-making software and spreadsheet in solving actuarial problems

To develop and use decision-making software and spreadsheets for actuarial problems, you can follow these steps:

• Identify the actuarial problem: Clearly define the actuarial problem you want to solve, such as pricing a new insurance product, analyzing mortality rates, or estimating reserves.
• Collect and organize relevant data: Gather the necessary data for your problem, ensuring it is accurate and complete. Organize the data in a structured format that can be easily used in software or spreadsheet tools.
• Choose appropriate software or spreadsheet tool: Depending on the complexity of the problem, select the most suitable software or spreadsheet tool. Excel, R, Python, and specialized actuarial software like Prophet or Emblem can be utilized based on the specific requirements.
• Develop models or algorithms: Design and develop the necessary models or algorithms to solve the actuarial problem. This may involve utilizing statistical methods, actuarial principles, or machine learning techniques, depending on the problem at hand.
• Implement the solution: Implement your models or algorithms in the chosen software or spreadsheet tool. This may involve writing code, creating formulas, or utilizing built-in functions to perform calculations and generate results.
• Test and validate the solution: Verify the accuracy and reliability of your solution by testing it with sample data or comparing it with known results. Make any necessary adjustments or refinements to improve the performance of your solution.
• Document and present the findings: Document your methodology, assumptions, and results in a clear and concise manner. Use appropriate charts, tables, and visualizations to present your findings effectively.

Assignment Task 3 : Formulate, analyze and interpret data.

To formulate, analyze, and interpret data in the context of actuarial work, you can follow these steps:

• Define the research question or objective: Clearly articulate the research question or objective that you aim to address through your data analysis. This could be related to pricing, risk assessment, mortality analysis, or any other actuarial topic.
• Gather and clean the data: Collect relevant data from reliable sources, ensuring its accuracy and completeness. Clean the data by addressing missing values, outliers, and inconsistencies.
• Formulate a data analysis plan: Determine the appropriate statistical techniques, models, or methods to analyze the data based on your research question. This could include regression analysis, survival analysis, time series analysis, or other statistical approaches commonly used in actuarial science.
• Apply data analysis techniques: Implement the chosen data analysis techniques using software tools such as Excel, R, Python, or specialized actuarial software. Perform the necessary calculations, estimations, and modeling to derive insights from the data.
• Interpret the results: Analyze the output of your data analysis and interpret the findings in the context of the research question. Clearly explain the implications of the results and any limitations or assumptions made during the analysis.
• Validate and assess the reliability of the findings: Assess the reliability of your findings by validating them using appropriate statistical tests, sensitivity analyses, or comparisons with industry benchmarks. Address any potential biases or limitations in the data or analysis.
• Present the results and conclusions: Communicate your findings in a clear and concise manner through reports, presentations, or visualizations. Use charts, graphs, and tables to effectively convey the key insights and conclusions drawn from the data analysis.

Remember to always document your methodology, assumptions, and sources of data to ensure transparency and reproducibility in your actuarial analysis.

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