I’ve collected raw accelerometer and gyroscope logs straight from an iPhone (CoreMotion CSV format) and now need a clear, well-documented statistical summary of that data. The goal is to understand central tendency, spread, correlation between axes, and any noticeable trends over time for both sensors. Please clean the dataset, handle missing or noisy readings, and then produce descriptive statistics (mean, median, variance, standard deviation, covariance), visualisations that highlight key insights (time-series plots, histograms, perhaps a correlation heat map), and a concise written interpretation of what the numbers show. I’m comfortable with Python, so a Jupyter Notebook built with pandas, NumPy, SciPy and Matplotlib or Seaborn is ideal. If you prefer R or MATLAB, that’s fine too—just keep the code readable and reproducible. Deliverables • Cleaned data file in the same structure as the original • Well-commented analysis notebook or script • Exported graphs (PNG or PDF) • Short report (1-2 pages) summarising findings and highlighting anything unexpected No machine-learning modelling is required; this is purely a statistical summary. Let me know if you need a sample of the data to estimate effort or clarify assumptions.