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Data Analysis & Statistics Workshop
Home
Labs
Lab 1.1 Getting started: Matlab and Data Analysis/Stats basics
Lab 1.2 Variables, Functions, and Simple Plots
Lab 1.3 More plotting and (dot) m-files
Lab 1.4 M-file Management; Differences in cumulative histograms
Lab 1.5 Did my drug really work? Statistical inference
Lab 1.6 What was the impact of my drug on average?
Lab 1.7 Basic sample descriptors; Tinkering with Plots
Lab 1.8 How well did my drug do? Variance explained and discriminability
Lab 2.1 Describing data with fits (models)
Lab 2.2 Using fitting as a tool, not like a fool
Lab 2.3 Creating robust index values
Lab 2.4 Dealing with a truckload of data
Lab 3.1 Time series: correlation, feature detection, rates
Lab 3.2 Frequencies and Fourier analysis
Lab 3.3 Convolution and filtering
Lab 4.1 Basic image representations
Lab 4.2 Digital image representations of the physical world
Lab 4.3 Image analysis: Regions of interest
Lab 4.4 Functional imaging
Lab 5.1 High-dimensional space: data points as vectors
Lab 5.2 High-dimensional space: clustering and dimensionality reduction
Lab 5.3 High-dimensional space: interpolation; how PCA works
Handouts/videos
Announcements
2013-07-15
Course Calendar
Overcoming bias in multiple comparisons
Topics covered
Useful Resources/Links
Using Brandeis computer clusters outside of class
Videos
Data Analysis & Statistics Workshop
Home
Labs
Lab 1.1 Getting started: Matlab and Data Analysis/Stats basics
Lab 1.2 Variables, Functions, and Simple Plots
Lab 1.3 More plotting and (dot) m-files
Lab 1.4 M-file Management; Differences in cumulative histograms
Lab 1.5 Did my drug really work? Statistical inference
Lab 1.6 What was the impact of my drug on average?
Lab 1.7 Basic sample descriptors; Tinkering with Plots
Lab 1.8 How well did my drug do? Variance explained and discriminability
Lab 2.1 Describing data with fits (models)
Lab 2.2 Using fitting as a tool, not like a fool
Lab 2.3 Creating robust index values
Lab 2.4 Dealing with a truckload of data
Lab 3.1 Time series: correlation, feature detection, rates
Lab 3.2 Frequencies and Fourier analysis
Lab 3.3 Convolution and filtering
Lab 4.1 Basic image representations
Lab 4.2 Digital image representations of the physical world
Lab 4.3 Image analysis: Regions of interest
Lab 4.4 Functional imaging
Lab 5.1 High-dimensional space: data points as vectors
Lab 5.2 High-dimensional space: clustering and dimensionality reduction
Lab 5.3 High-dimensional space: interpolation; how PCA works
Handouts/videos
Announcements
2013-07-15
Course Calendar
Overcoming bias in multiple comparisons
Topics covered
Useful Resources/Links
Using Brandeis computer clusters outside of class
Videos
More
Home
Labs
Lab 1.1 Getting started: Matlab and Data Analysis/Stats basics
Lab 1.2 Variables, Functions, and Simple Plots
Lab 1.3 More plotting and (dot) m-files
Lab 1.4 M-file Management; Differences in cumulative histograms
Lab 1.5 Did my drug really work? Statistical inference
Lab 1.6 What was the impact of my drug on average?
Lab 1.7 Basic sample descriptors; Tinkering with Plots
Lab 1.8 How well did my drug do? Variance explained and discriminability
Lab 2.1 Describing data with fits (models)
Lab 2.2 Using fitting as a tool, not like a fool
Lab 2.3 Creating robust index values
Lab 2.4 Dealing with a truckload of data
Lab 3.1 Time series: correlation, feature detection, rates
Lab 3.2 Frequencies and Fourier analysis
Lab 3.3 Convolution and filtering
Lab 4.1 Basic image representations
Lab 4.2 Digital image representations of the physical world
Lab 4.3 Image analysis: Regions of interest
Lab 4.4 Functional imaging
Lab 5.1 High-dimensional space: data points as vectors
Lab 5.2 High-dimensional space: clustering and dimensionality reduction
Lab 5.3 High-dimensional space: interpolation; how PCA works
Handouts/videos
Announcements
2013-07-15
Course Calendar
Overcoming bias in multiple comparisons
Topics covered
Useful Resources/Links
Using Brandeis computer clusters outside of class
Videos
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