Topics covered

Units of the course:
  1. Did my drug work?
    1. Basic use of Matlab, including variables, functions
    2. Plotting (bar plots, scatter plots, histograms, cumulative histograms)
    3. Statistical inference
    4. Comparing distributions (Kolmogorov-Smirnov test), means (T-test)
    5. ANOVA
  2. Fits and indexes
    1. How to create a fit (linear fits, non-linear fits)
    2. Dealing with a mountain of data while avoiding garbage in / garbage out
    3. Calculating robustness/uncertainty for fits and index values
  3. Time series
    1. Correlations in time
    2. Feature detection
    3. Fourier analysis / frequency analysis
    4. Convolution and filtering
  4. Image processing
    1. Digital representations of images in the world
    2. Feature detection and extraction
    3. Functional imaging (time series of images)
  5. High-dimensional data
    1. Clustering
    2. Dimensionality reduction (including principle component analysis)
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