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Course Detail

Course Name Categorical Data Analysis
Course Code 24ASD632
Program M.Sc. in Applied Statistics and Data Analytics
Credits 3
Campus Coimbatore , Kochi

Syllabus

Categorical Data-nominal and ordinal random variables.

Two-way contingency tables: Table structure for two dimensions. Ways of comparing
proportions. Measures of associations-odds ratio. Sampling distributions. Goodness-of-fit
tests, testing of independence. Exact and large sample inference.

Three-way contingency tables, Partial associations, Cochran-Mantel-Haenszel methods.
Conditional association and related inference.

Generalized Linear Models (GLMs): components of a GLM.
Logisitc regression models for binary data, inference for logistic regression models, multiple
logistic regression with qualitative predictors, exact inference for logistic regression, sample
size and power of test.

Loglinear models for two-way and three-way contingency tables, inference for loglinear
models, the connection between loglinear-logit regression models. Multicategory logit models for nominal responses, cumulative logit models for ordinal
responses.

Objectives and Outcomes

Course Outcomes:

CO1: Understand the Categorical Data-nominal and ordinal random variables.

CO2: Understand the two-way contingency tables.

CO3: Understand the three-way contingency tables.

CO4: Understand the basic of Generalized Linear Models

CO-PO Mapping:

PO1

PO2

PO3

PO4

PO5

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

CO1

2

2

2

2

2

2

1

1

CO2

3

3

2

2

2

2

1

1

CO3

2

2

3

2

2

2

1

1

CO4

3

3

3

2

2

2

1

1

Text Books / References

Text Books / Reference Books:
1. Agresti, A., Categorical Data Analysis, 3rd Edition, Wiley, New York, 2013.
2. Agresti, A., An Introduction to Categorical Data Analysis, 3rd Edition, Wiley, New York, 2019.
3. Andersen, E.B., The Statistical Analysis of Categorical Data, Springer-Verlag, Berlin, 1994.
4. Santner, T.J. and Duffy, D., The Statistical Analysis of Discrete Data, Springer-Verlag, New York, 1989.

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