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Training - Courses

ST01: 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.

Course Length - 1  day

Price - $650.00

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