ST408 : Categorical Data Analysis

Department

Department of Statistics

Academic Program

Bachelor in Statistics

Type

Compulsory

Credits

04

Prerequisite

ST209ST308

Overview

  1. · Develop the student's experience in the description and statistical inference of tables with different directions.
  2. · Expand student experience in building and interpreting models for binary response data
  3. · Tests for three-way tables.
  4. · Identifying logistic regression and its applications

Intended learning outcomes

(Course intended learning outcomes)

A.1

The student's knowledge of the analysis of counting data and relative proportion.

A.2

The student's knowledge of topics involving correlation tests in bidirectional tables.

A.3

Knowledge of correlation scales, Cochran-Mantal-Haenzel

A.4

Learn about tests for three-way tables, generalized linear models andthe ability to understand logistic regression

a. Mental (skills)

B.1

Expansion of the student's mental perceptions in data analysis.

B.2

Improve the student's ability to face the analyzes of different tables.

B.3

Providing the student with new tests that increase his ability to understand and analyze dual-response data.

B4

The student acquires the ability to understand logistic regression

In. Practical & Professional (Skills)

C.1

Use proportional counting and proportionality data analysis

C.2

The student's knowledge of the analyzes of different tables.

C3

The student's knowledge of new tests increases his ability to understand and analyze two- and three-response data.

C4

The student's knowledge of the concept of logistic regression

c. Generic (and transferable skills)

D.1

Ability to write reports and scientific articles, make oral presentations.

D.2

Ability to analyze two-response and three-way data.

D.3

Ability to use modern technological tools in data analysis applications

D4

Ability to understand logistic regression

Teaching and learning methods

Lectures

· Solve exercises and assignments.

· Loops fordiscussion.

Methods of assessments

(Assessment table)

Rating No.

Evaluation methods

Evaluation Duration

Evaluation weight

Percentage

Rating Date (Week)

Reviews

First Assessment

Duties in the form of exercises

10 %

Second Assessment

Two midterm exams

40 %

Final Evaluation

Final Exam

50 %

Total

100 degree

100%

Course (contents)

Scientific topic

Number of Hours

Lecture

Exercises

Number of weeks

Analysis of proportional counting and proportionality data

10

6

4

2

Correlation tests in bidirectional tables

15

9

6

3

Correlation scales, Cochran-Mantal-Haenzel

15

9

6

3

Tests for three-way tables and multiple linear model

15

9

6

3

Logistic regression, logarithmic linear model.

15

9

6

3

(References )

Bibliography

Publisher

Version

Author

Where it is located

Rapporteur notes

Explanatory note prepared by the course instructor

Textbooks

an introduction to categorical data analysis (2nd ed)

Agresti, A.

Willy

Help Books

Scientific Journals

Internet Sites

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Other