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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Ordinal Data Analysis: Statistical Perspective with Applications

Ordinal Data Analysis: Statistical Perspective with Applications

Dasgupta, Nairanjana
Morrison, Jillian

Hardcover

Probability & Statistics

ISBN10: 0367855909
ISBN13: 9780367855901
Publisher: CRC Press
Published: Jun 4 2024
Pages: 190
Weight: 1.03
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English

This book is a step-by-step data story for analyzing ordinal data from start to finish. The book is for researchers, statisticians and scientists who are working with datasets where the response is ordinal. This type of data is common in many disciplines, not just in surveys (as is often thought). For example, in the biological sciences, there is an interest in understanding and predicting the (growth) stage (of a plant or animal) based on a multitude of factors. Likewise, ordinal data is common in environmental sciences (for example, stage of a storm), chemical sciences (for example, type of reaction), physical sciences (for example, stage of damage when force is applied), medical sciences (for example, degree of pain) and social sciences (for example, demographic factors like social status categorized in brackets). There has been no complete text about how to model an ordinal response as a function of multiple numerical and categorical predictors. There has always been a reluctance and reticence towards ordinal data as it lies in a no-man's land between numerical and categorical data.

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