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I need assistance with cleaning and analyzing survey data for research on postpartum anxiety. Data Cleaning Tasks: - Identifying and handling missing values - Dealing with non-normally distributed data Data Analysis Tasks: - Descriptive statistics - Inferential statistics - Regression analysis Mediation analysis using PROCESS MACRO Ideal Skills & Experience: - Proficiency in statistical software (e.g., R, SPSS, MPlus) - Strong background in handling survey data - Experience with research data analysis - Knowledge of postpartum anxiety research is a plus

Project requirements 1) Submission package Report files Part 1 report: maximum 2 pages Part 2 report: maximum 6 pages Page limits include figures and tables Page limits exclude title page, table of contents, and references The report must include explanations suitable for readers not familiar with programming Report must be submitted as PDF (or other allowed document format as specified by your portal) Code files (reproducible) Python code must be provided as Jupyter notebook(s) (.ipynb) R code must be provided as RMarkdown (.Rmd) if required by the brief Code must be runnable by someone else to reproduce your results If you reuse outputs or cleaned data from earlier questions, you must reference them clearly Submission location All relevant files must be submitted to the des...

I have several years of historical sales records spread across CSV files, Excel workbooks, and a database. I want you to turn that mixed-source information into a clean, consistent dataset, explore it for trends and seasonality, and then build a machine-learning model that can reliably project future sales. Data preparation must cover every stage—handling missing values, normalising numeric fields, and performing any transformations needed to feed the algorithms. Once the data is tidy, run an exploratory analysis so I can clearly see the patterns that drive revenue, especially how previous sales, marketing spend, and seasonal shifts interact. For modelling, I am open to linear regression, Random Forest, ARIMA, or another regression-based technique you can justify in the report. The...