### Abstract

Categorical data are data that capture a characteristic of an experimental unit (such as a tissue specimen) rather than a numerical value. In this chapter, we first describe types of categorical data (nominal and ordinal) and how these types of data are distributed (binomial, multinomial, and independent multinomial). Next, methods for estimation and making statistical inferences for categorical data in commonly seen situations are presented. This includes approximation of the binomial distribution with a normal distribution, estimation and inference for one and two binomial samples, inference for 2 x 2 and R x C contingency tables, and estimation of sample size. Relevant data examples, along with discussions of which study designs generated the data, are presented throughout the chapter.

Original language | English |
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Pages (from-to) | 73-88 |

Number of pages | 16 |

Journal | Methods in molecular biology (Clifton, N.J.) |

Volume | 404 |

State | Published - 2007 |

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### ASJC Scopus subject areas

- Molecular Biology
- Genetics

### Cite this

**Statistical inference on categorical variables.** / Perkins, Susan.

Research output: Contribution to journal › Article

*Methods in molecular biology (Clifton, N.J.)*, vol. 404, pp. 73-88.

}

TY - JOUR

T1 - Statistical inference on categorical variables.

AU - Perkins, Susan

PY - 2007

Y1 - 2007

N2 - Categorical data are data that capture a characteristic of an experimental unit (such as a tissue specimen) rather than a numerical value. In this chapter, we first describe types of categorical data (nominal and ordinal) and how these types of data are distributed (binomial, multinomial, and independent multinomial). Next, methods for estimation and making statistical inferences for categorical data in commonly seen situations are presented. This includes approximation of the binomial distribution with a normal distribution, estimation and inference for one and two binomial samples, inference for 2 x 2 and R x C contingency tables, and estimation of sample size. Relevant data examples, along with discussions of which study designs generated the data, are presented throughout the chapter.

AB - Categorical data are data that capture a characteristic of an experimental unit (such as a tissue specimen) rather than a numerical value. In this chapter, we first describe types of categorical data (nominal and ordinal) and how these types of data are distributed (binomial, multinomial, and independent multinomial). Next, methods for estimation and making statistical inferences for categorical data in commonly seen situations are presented. This includes approximation of the binomial distribution with a normal distribution, estimation and inference for one and two binomial samples, inference for 2 x 2 and R x C contingency tables, and estimation of sample size. Relevant data examples, along with discussions of which study designs generated the data, are presented throughout the chapter.

UR - http://www.scopus.com/inward/record.url?scp=43749123251&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=43749123251&partnerID=8YFLogxK

M3 - Article

C2 - 18450046

AN - SCOPUS:43749123251

VL - 404

SP - 73

EP - 88

JO - Methods in Molecular Biology

JF - Methods in Molecular Biology

SN - 1064-3745

ER -