Isbn: 9781108418539 - a practical guide to time series analysis (16 risultati)

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: NEW.

Hardback. Condizione: New. Understanding change over time is a critical component of social science. However, data measured over time - time series - requires their own set of statistical and inferential tools. In this book, Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications using examples. The guide outlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly  explain their statistical analyses to a broad audience.…

Hardcover. Condizione: Brand New. 1st edition. 552 pages. 6.00x1.38x9.00 inches. In Stock.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Understanding change over time is a critical component of social science. However, data measured over time - time series - requires their own set of statistical and inferential tools. Inthis book,Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications usingexamples. Theguideoutlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly explain their statistical analyses to a broad audience. …

Hardback. Condizione: New. Understanding change over time is a critical component of social science. However, data measured over time - time series - requires their own set of statistical and inferential tools. In this book, Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications using examples. The guide outlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly  explain their statistical analyses to a broad audience.…

Condizione: New. 2026. hardcover. . . . . . Books ship from the US and Ireland.

Condizione: New. 2026. hardcover. . . . . .

Hardcover. Condizione: new. Hardcover. Understanding change over time is a critical component of social science. However, data measured over time time series requires their own set of statistical and inferential tools. In this book, Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications using examples. The guide outlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly explain their statistical analyses to a broad audience. Our applied guide is for students analysing data over time. For example, approval ratings, economic measures, and international conflicts. Time series data requires its own set of advanced statistical tools which we outline as simply as possible. Detailed examples help readers navigate the complicated process of learning from temporal data. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condizione: new. Hardcover. Understanding change over time is a critical component of social science. However, data measured over time time series requires their own set of statistical and inferential tools. In this book, Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications using examples. The guide outlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly explain their statistical analyses to a broad audience. Our applied guide is for students analysing data over time. For example, approval ratings, economic measures, and international conflicts. Time series data requires its own set of advanced statistical tools which we outline as simply as possible. Detailed examples help readers navigate the complicated process of learning from temporal data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condizione: Neu. A Practical Guide to Time Series Analysis | Suzanna Linn (u. a.) | Buch | Englisch | 2026 | Cambridge University Press | EAN 9781108418539 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Hardcover. Condizione: new. Hardcover. Understanding change over time is a critical component of social science. However, data measured over time time series requires their own set of statistical and inferential tools. In this book, Suzanna Linn, Matthew Lebo, and Clayton Webb explain the most commonly used time series models and demonstrate their applications using examples. The guide outlines the steps taken to identify a series, make determinations about exogeneity/endogeneity, and make appropriate modelling decisions and inferences. Detailing challenges and explanations of key techniques not covered in most time series textbooks, the authors show how navigating between data and models, deliberately and transparently, allows researchers to clearly explain their statistical analyses to a broad audience. Our applied guide is for students analysing data over time. For example, approval ratings, economic measures, and international conflicts. Time series data requires its own set of advanced statistical tools which we outline as simply as possible. Detailed examples help readers navigate the complicated process of learning from temporal data. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…