STAT 469

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Analysis of Correlated Data

StatisticsCollege of Computational, Mathematical, & Physical Sciences

Course Description

IID regression, heterogenous variances, SARIMA models, longitudinal data, point and areally referenced spatial data.

When Taught

Winter

Min

3

Fixed/Max

3

Fixed

3

Fixed

0
Prerequisite
Complete ALL of the following Courses:
  • 11842-001
    AND
    11843-001

Title

Define Functions

Learning Outcome

Define the autocovariance and autocorrelation functions

Title

Order of an ARIMA

Learning Outcome

Select the order of an ARIMA model from the sample ACF and sample PACF

Title

Define Weak Stationarity

Learning Outcome

Define weak stationarity

Title

ARMA

Learning Outcome

Define an ARMA (p, q) process

Title

Define Process

Learning Outcome

Define white noise process

Title

Fit an ARIMA

Learning Outcome

Fit an ARIMA (p, d, q) model and generate forecasts with prediction intervals in R

Title

AR and MA Model

Learning Outcome

Derive the mean, autocovariance, and autocorrelation of an AR and MA model