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MLST: Statistical Methods in MATLAB

This course provides an introduction to statistical tools in MATLAB, Statistics Toolbox, and the Curve Fitting Toolbox including:

Data file input and output
Handling large and incommensurate data sets
Computing descriptive statistics
Statistical plotting and visualization
Fitting distributions to data
Bivariate regression
Random number generators, simulations, and hypothesis tests

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	Detailed course outline

Day 1 of 1
Introduction	Objectives: Obtain a quick overview of The MathWorks and the family of products Discuss course set-up, materials, and logistics Provide a “big picture” view of the course ahead
Data and Statistics	Objective: Learn to work with data in the MATLAB environment, compute basic descriptive statistics, and visualize data in a variety of ways What is statistics? Statistical sampling and modeling Statistical questions Data analysis
Working with data	Incommensurate data Missing data
Descriptive statistics	Measures of center, spread, and shape
Statistical plotting	Histograms, scatter plots, and box plots Grouped data
Distributions and Bootstrapping	Objective: Explore the variety of probability distributions available in the Statistics Toolbox
Distribution concepts	Discrete distributions Continuous distributions Distributions in the Statistics Toolbox Distribution parameters Computing probabilities
Data and distributions	Sampling distributions Choosing a distribution Parameter estimation Nonparametric density functions Bootstrapping and simulation Distribution testing
Exercise	Distribution diagnostics
Regression Analysis	Objective: Explore regression analysis for bivariate data Regression concepts Predictors and responses Linear and nonlinear models Scatter plots Correlation and covariance
Linear methods	Quantiles and quantile plots Solving systems of linear equations with the backslash operator Linear least squares Polynomial fitting Graphical user interface tools for linear regression Curve Fitting Toolbox Generalized linear models
Nonlinear methods	Graphical user interface tools for nonlinear regression Using the Curve Fitting Toolbox for nonlinear regression
Exercise	National debt
Hypothesis Tests	Objective: Explore the various hypothesis test within the toolbox Terminology Assumptions Tests in the Statistics Toolbox

Prerequisites

Working knowledge of the MATLAB language and basic statistics.

Class Times: September 28-30, 2010: 8:30a - 12:30p (GMT-4:00)

Please Note: A 1 hour test session will be scheduled on the first day of class. This test session will cover viewing and audio troubleshooting as well as software installation (content will be presented during the remaining days). It is highly recommended that you attend this session to ensure a successful start to the class.

Course Length - 2 half-days

Price - $650.00

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