Executive summary Introduction and objectives Methodology description Results and findings Conclusions and recommendations Data Visualizations: Graphs, charts, and plots to illustrate key findings Infographics summarizing data insights Statistical Analysis Output: Tables of statistical results (e.g., regression outputs, p-values, confidence intervals) Summary statistics (mean, median, mode, standard deviation, etc.) Code and Scripts: Well-documented code used for data analysis (e.g., R, Python, SAS) Scripts for reproducibility of results Data Sets: Cleaned and processed datasets Original data with metadata or codebook Presentations: Slide deck summarizing key findings for stakeholder meetings Oral presentation of results (if required) Recommendations Report: Actionable insights based on the data analysis Suggestions for future research or data collection Technical Documentation: Documentation explaining methodologies, assumptions, and limitations Guidance on interpreting results Follow-Up Plan: Suggested next steps or additional analyses if needed Framework for ongoing data monitoring or evaluation Consultation: A follow-up meeting to discuss results and address any questions or concerns These deliverables help ensure that clients have a comprehensive understanding of the analysis conducted and the implications of the findings.