Large-scale natural gradient tracer test in sand and gravel, Cape Cod, Massachusetts: 1. Experimental design and observed tracer movement

1991 ◽  
Vol 27 (5) ◽  
pp. 895-910 ◽  
Author(s):  
Denis R. LeBlanc ◽  
Stephen P. Garabedian ◽  
Kathryn M. Hess ◽  
Lynn W. Gelhar ◽  
Richard D. Quadri ◽  
...  
1991 ◽  
Vol 27 (5) ◽  
pp. 911-924 ◽  
Author(s):  
Stephen P. Garabedian ◽  
Dennis R. LeBlanc ◽  
Lynn W. Gelhar ◽  
Michael A. Celia

1996 ◽  
Vol 32 (3) ◽  
pp. 519-532 ◽  
Author(s):  
David L. Rudolph ◽  
R. Gary Kachanoski ◽  
Michael A. Celia ◽  
Denis R. LeBlanc ◽  
Jonathon H. Stevens

2011 ◽  
Vol 6 (2) ◽  
pp. 252-277 ◽  
Author(s):  
Stephen T. Ziliak

AbstractStudent's exacting theory of errors, both random and real, marked a significant advance over ambiguous reports of plant life and fermentation asserted by chemists from Priestley and Lavoisier down to Pasteur and Johannsen, working at the Carlsberg Laboratory. One reason seems to be that William Sealy Gosset (1876–1937) aka “Student” – he of Student'st-table and test of statistical significance – rejected artificial rules about sample size, experimental design, and the level of significance, and took instead an economic approach to the logic of decisions made under uncertainty. In his job as Apprentice Brewer, Head Experimental Brewer, and finally Head Brewer of Guinness, Student produced small samples of experimental barley, malt, and hops, seeking guidance for industrial quality control and maximum expected profit at the large scale brewery. In the process Student invented or inspired half of modern statistics. This article draws on original archival evidence, shedding light on several core yet neglected aspects of Student's methods, that is, Guinnessometrics, not discussed by Ronald A. Fisher (1890–1962). The focus is on Student's small sample, economic approach to real error minimization, particularly in field and laboratory experiments he conducted on barley and malt, 1904 to 1937. Balanced designs of experiments, he found, are more efficient than random and have higher power to detect large and real treatment differences in a series of repeated and independent experiments. Student's world-class achievement poses a challenge to every science. Should statistical methods – such as the choice of sample size, experimental design, and level of significance – follow the purpose of the experiment, rather than the other way around? (JEL classification codes: C10, C90, C93, L66)


2019 ◽  
Vol 8 (2) ◽  
pp. 246-256
Author(s):  
Rina Wahyuningsih ◽  
Sri Sukaesih ◽  
Endah Peniati

This study aims to describe the types of learning resources used previously at SMA N 3 Salatiga, describe the feasibility of Biomagz Based on Local Wisdom, and test the effectiveness of Biomagz Based on Local Wisdom on learning outcomes and student’s environmental care attitude. The method used is research development (R & D). Products are validated by material and media validators, and revised before being tested. Small-scale trials (readability test) use 10 students from class X MIPA 1, while large-scale trials use class X MIPA 2 with the experimental design Pre-experimental Design with the type of Pre-test and Post-test One Group Design. The results of the study show the variety of learning resources used previously including biological, teacher, internet, biology books, and the environment around students. The Feasibility of Biomagz Based on Local Wisdom obtained an average score of 92.21% with very decent criteria. Large-scale trials with an average N-gain value 0.49 in the medium category, the average classical completeness is 85.29%, and the environment care attitude of students is based on the observation result of 92.9% with a high category and the result of the inter-student assessment is 86, 18% with a high category. Based on the results of this study, it can be concluded that Biomagz Based Local Wisdom is well worth and effective on learning outcomes and student’s environmental care attitude.


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