MTH (0144) 566 - Advanced Statistical Procedures

Credits: 3.00

Students are exposed to advanced procedures in statistical analysis. Students will explore and apply time series analysis, discrete data analysis, and the analysis of multivariate data.

Prerequisite 1: MTH 560
Free Note: Open only to students in the MS in Mathematics.

Students will:
●   Apply moving average models and partial autocorrelation as foundations for analysis of time series data. This will be assessed by Quiz 1 and the mid-term examination.
●   Use smoothing and removing trends when working with time series data. This will be assessed by Quiz 2 and the mid-term examination.
●   Implement ARMA and ARIMA time series models. This will be assessed by Quiz 3 and the mid-term examination.
●   Identify and interpret various patterns for intervention effects. This will be assessed by Quiz 3 and the mid-term examination.
●   Examine the analysis of repeated measures design. This will be assessed by Quiz 3 and the mid-term examination.
●   Apply the concept of likelihood. This will be assessed by Quiz 4 and the mid-term examination.
●   Implement tests for one-way tables using Pearsons X2 and likelihood-ratio G2 statistics. This will be assessed by Quiz 4 and the mid-term examination.
●   Using contingency tables including 2 × 2 and r × c tables, tests for independence and homogeneity of proportions, Fishers exact test, odds ratio and logit, other measures of association. This will be assessed by Quiz 4 and the mid-term examination.
●   Use 3-way tables in full independence and conditional independence contexts, collapsing and understanding Simpson’s paradox. This will be assessed by Quiz 4 and the mid-term examination.
●   Use polytomous logit models for ordinal and nominal response. This will be assessed by Quiz 4 and the mid-term examination.
●   Use loglinear models (and graphical models) for multi-way tables. This will be assessed by Quiz 4 and the mid-term examination.
●   Work with multivariate data and its graphical display. This will be assessed by Quiz 5 and the final examination.
●   Understand the multivariate normal distribution and how it is used. This will be assessed by Quiz 5 and the final examination.
●   Explain the properties of sample mean vectors and correlation in multivariate data contexts. This will be assessed by Quizzes 6-8 and the final examination.
●   Explain the role that partial correlation may play in multivariate contexts. This will be assessed by Quiz 8 and the final examination.
●   Explain how data reduction techniques can be used to generate more meaningful interpretation. This will be assessed by Quiz 8 and the final examination.
●   Use principal component analysis, factor analysis, and canonical correlation analysis. This will be assessed by Quiz 9 & 10, and the final examination.
●   Explain the implications involved in making inferences in multivariate contexts. This will be assessed by Quiz 9 & 10, and the final examination.
●   Use discriminant analysis, MANOVA, and repeated measures on multivariate data. This will be assessed by Quiz 9 & 10, and the final examination.