Final answer:
To plan an effective audit data analytics procedure, it's necessary to identify the financial statement areas to be audited, define the purpose and contribution of the analytics to the audit, and determine the audit population scope. All choices provided in the question are correct and crucial for a robust audit plan.
Step-by-step explanation:
When planning an audit data analytics procedure, several key issues are crucial to consider. Firstly, determine what financial statement items, accounts, or disclosures and related assertions are being audited. This involves identifying the specific areas of the financial statements that the analytics will focus on and the assertions related to completeness, accuracy, and validity. Secondly, ascertain the overall purpose of the audit data analytics procedure and understand how it will contribute to the effectiveness of the audit process, ensuring that the analytics serve a clear objective and are aligned with the audit goals. Lastly, identify the audit population being analyzed or tested using audit data analytics, which means defining the scope and nature of the data set that will be subjected to analytical procedures.
It is also important to consider the validity of the sources, assess any potential biases, and ensure adherence to guidelines for proper conduct. Analyzing data involves deciding the criteria for its use and applying those criteria effectively. Therefore, all of the choices provided in the question are correct and interrelated when it comes to planning an effective audit data analytics procedure.