Using an SAS summary paper that presents your sales data analysis, incorporating real-world applications and insights. Your analysis should include:

Statistical Analysis Output and Interpretation :

• Summarize the output and interpretation of the statistical analyses conducted on the sales data. This may include descriptive statistics, hypothesis testing, confidence intervals, or any other relevant analyses.
• Provide clear explanations of the findings and their implications for understanding sales performance.

Factors Relevant to Analysis :

• Discuss the factors you considered relevant to your analysis, such as the source fields or attributes used in the dataset.
• Explain why these factors were chosen and how they contribute to understanding sales trends and patterns.

Identification of Potential Risks :

• Identify any potential inherent risks associated with the methods used in your analysis.
• Discuss how these risks could impact the validity or reliability of your findings and interpretations.

Validation of Assumptions :

• Describe the checks performed to validate all assumptions necessary for the selected hypothesis testing and confidence interval methods.
• Explain how these checks ensure the robustness and accuracy of your statistical analyses.

Persuasive Argument and Recommendation:

• Create a persuasive argument advocating for a specific viewpoint or recommendation based on your analysis of the sales data.
• Support your argument with evidence and insights derived from the statistical analysis.
• Consider the target audience and tailor your communication style and vocabulary to effectively convey your message