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| Semester: | Fall 2020 |
| Number: | 0144-566-001 |
| Instructor: | Joshua Hiller |
| Days: | Wednesday 6:00 pm - 8:30 pm |
| Note: | Online, Synchronous |
| Location: | Online |
| Credits: | 3 |
| Notes: |
Only Open To Students In The Ms In Mathematics |
| Course Materials: | View Text Books |
| Description: |
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. |
| Learning Goals: |
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 inv *The learning goals displayed here are those for one section of this course as offered in a recent semester, and are provided for the purpose of information only. The exact learning goals for each course section in a specific semester will be stated on the syllabus distributed at the start of the semester, and may differ in wording and emphasis from those shown here. |
| Prerequisites: |
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