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Evaluating the Effectiveness of Metal Pollution Controls in a Smelter by Using Metallothionein and Other Biochemical Responses in Fish
Published in Michael C. Newman, Alan W. McIntosh, Metal Ecotoxicology, 2020
John F. Klaverkamp, Michael D. Dutton, Henry S. Majewski, Robert V. Hunt, Laurie J. Wesson
Analyses of variance were computed using the GLM procedure of the Statistical Analysis System.34 A two-way factorial arrangement using group and sex was applied to test for significant differences in fish from the terminal sampling. Differences between group means were examined using Tukey’s Studentized Range test. White suckers from sampling sites in the vicinity of the smelter were compared with reference fish from the most distant lake (Twin Lake). Statistically significant differences between groups have been indicated at p <0.05 and ρ <0.10. Multiple regression analysis was used to develop predictive equations for metal concentrations in liver and kidney of fish, as well as to determine the relationship between surficial sediment metals and limnological variables. Pearson product-moment correlation coefficients were used to establish significant (p <0.1) relationships between measured biochemical parameters and metal levels in either surficial sediment or fish tissue.
Distribution-Level Case Study: Forecasting of Air Freight Delays
Published in Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Puerto-Santana, Concha Bielza, Industrial Applications of Machine Learning, 2019
Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Puerto-Santana, Concha Bielza
where qα $ q_{\alpha } $ are critical values based on the Studentized range statistic divided by 2 $ \sqrt{2} $ . A table of values can be found in Demšar (2006). More advanced methods are discussed in further detail in Demšar (2006); García and Herrera (2008).
Design of experiments and analysis of variance
Published in Andrew Metcalfe, David Green, Tony Greenfield, Mahayaudin Mansor, Andrew Smith, Jonathan Tuke, Statistics in Engineering, 2019
Andrew Metcalfe, David Green, Tony Greenfield, Mahayaudin Mansor, Andrew Smith, Jonathan Tuke
The studentized range was introduced by WS Gosset (Student) in 1927 and its use as a follow up procedure to an ANOVA was described by John Tukey in 1949. The studentized range statistic is defined as the ratio of the range of an SRS of size m from a normal distribution to an independent estimate of the standard deviation of that distribution based on ν degrees of freedom. So, the distribution has two parameters m and ν.
Sense-Making of Critical Incidents with Sentiment Analysis and Data Visualization
Published in Engineering Management Journal, 2018
Ashley Nolen Akerman, Larry Mallak, David Lyth
The intent of the statistical analysis was to identify differences in mean sentiment among hospitals, questions, and the interaction of questions and hospitals. The working assumption was that hospitals with mean sentiment values that were statistically higher or lower than their peer group would indicate potential cultural differences. Clues to these differences could be found by analyzing hospital and question interactions that deviated significantly from the overall sample. In order to identify these specific cases, a post-hoc review was conducted using Tukey’s studentized range test of adjusted means.
Bioprocessing and purification of extracellular L-asparaginase produced by endophytic Colletotrichum gloeosporioides and its anticancer activity
Published in Preparative Biochemistry & Biotechnology, 2023
Ling Sze Yap, Wai Leng Lee, Adeline Su Yien Ting
All experiments were performed in triplicates and data were reported as mean ± standard error (SE). Statistical analysis was performed using the software Statistical Package for the Social Sciences (SPSS) version 25. One-way ANOVA with Tukey’s Studentized Range Test (HSD (0.05)) was used to compare means with p-value < 0.05. Independent Samples Test with equal variances assumed were used to compared means with p-values <0.01, 0.001 and 0.0001.