《澳大利亞與新西蘭統計雜志》是由澳大利亞統計學會和新西蘭統計學會聯合主辦的國際期刊。它的目的是報告在統計方面的重大和新穎的貢獻，包括關于統計理論、方法論、應用和計算的文章。該雜志特別關注可以很容易地應用于現實問題的統計技術，以及重點放在澳大利亞的應用論文。在澳大利亞統計學會或新西蘭統計協會的會議上，提交給該雜志的優秀文章可被選為討論論文。雜志的主體分為三個部分。理論和方法科發表載有對統計學、計量經濟學和概率論的理論和方法作出原創性貢獻的論文，并尋找以實際問題為動機，并在這種情況下證明所提議的理論或方法的論文。人們對那些由真實數據驅動并以真實數據為例證的論文有著強烈的偏好。應用程序組發表論文，展示統計技術應用于科學、政府和工業界統計用戶所面對的問題。一個特別的重點是將新發展的統計方法應用于實際數據，并示范如何在一個應用領域更好地利用現有的統計方法。它試圖通過將統計方法置于背景中來幫助統計學教師。統計計算部分發表包含新算法、代碼片段或軟件描述(僅適用于開源軟件)的論文，通過計算的應用來增強該領域。優先考慮具有公開可用代碼和/或數據的論文，以及為解決實際問題而采用統計方法的論文。此外，適當的評論論文和文章的歷史和一般興趣將被考慮。該雜志還定期出版書評。

The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association.The main body of the journal is divided into three sections.The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data.The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context.The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems.In addition, suitable review papers and articles of historical and general interest will be considered. The journal also publishes book reviews on a regular basis.