01866 2200193 4500245007100000020002200071250001200093100001700105650002000122650002200142650001000164005001900174260003200193041001200225084001100237300002400248500139100272336000901663 aEnvironmental and ecological statistics with RcSong S. QianhText a978-1-4987-2872-0 aEd. 2nd aSong S. Qian aFakultas Teknik aTeknik Lingkungan aebook a20231011144651 aBoca RatonbCRC Pressc2017 aEnglish a618.92 axxiv, 535 halaman : aI learned statistics from Bayesian statisticians. As a result, I do not pay attention to hypothesis testing and p-values in my work. Likewise, I do not emphasize the use of them in my teaching. However, most students from my classes remember the term “statistically significant” (or p < 0.05) better than anything and check the R2 value when evaluating a regression model. I have talked to many of them on their experiences in learning and using statistics to understand why they seem to be naturally drawn to these numbers that few can explain clearly in plain language. I came to a satisfactory explanation around 2007 when I read slides of a presentation given by Dick De Veaux of Williams College entitled “Math is Music; Statistics is Literature.” (This presentation is now available on YouTube.) According to Dr. De Veaux, statistics is challenging to both students and instructors alike, because we want to teach not only the mechanical part of statistics, but also the process of making a judgment. As a statistics course is always counted as a quantitative methods class, students naturally view statistics as a mathematics class. But statistics is not mathematics. In a typical statistical class for environmental/ecological graduate students, we typically use very simple (but often tedious) mathematics. Students expect to learn statistics as they learn mathematics. atext01866 2200193 4500245007100000020002200071250001200093100001700105650002000122650002200142650001000164005001900174260003200193041001200225084001100237300002400248500139100272336000901663 aEnvironmental and ecological statistics with RcSong S. QianhText a978-1-4987-2872-0 aEd. 2nd aSong S. Qian aFakultas Teknik aTeknik Lingkungan aebook a20231011144651 aBoca RatonbCRC Pressc2017 aEnglish a618.92 axxiv, 535 halaman : aI learned statistics from Bayesian statisticians. As a result, I do not pay attention to hypothesis testing and p-values in my work. Likewise, I do not emphasize the use of them in my teaching. However, most students from my classes remember the term “statistically significant” (or p < 0.05) better than anything and check the R2 value when evaluating a regression model. I have talked to many of them on their experiences in learning and using statistics to understand why they seem to be naturally drawn to these numbers that few can explain clearly in plain language. I came to a satisfactory explanation around 2007 when I read slides of a presentation given by Dick De Veaux of Williams College entitled “Math is Music; Statistics is Literature.” (This presentation is now available on YouTube.) According to Dr. De Veaux, statistics is challenging to both students and instructors alike, because we want to teach not only the mechanical part of statistics, but also the process of making a judgment. As a statistics course is always counted as a quantitative methods class, students naturally view statistics as a mathematics class. But statistics is not mathematics. In a typical statistical class for environmental/ecological graduate students, we typically use very simple (but often tedious) mathematics. Students expect to learn statistics as they learn mathematics. atext