The Probable Error of a Mean

Differences in the microRNAs Levels of Raw Milk from Dairy Cattle Raised under Extensive or Intensive Production Systems

el qassim, L. A., Alonso, J., Zhao, K., Guillou, S. L., Díez, J., Vicente, F., Fernández‐Sanjurjo, M., Iglesias‐Gutiérrez, E., Guan, L. L., & Royo, L. J. (2022) · Veterinary Sciences · doi:10.3390/vetsci9120661 · Cited by 12

Use of Statistical Analyses in the Ophthalmic Literature

Lisboa, R. D. D. R., Meira-Freitas, D., Tatham, A. J., Marvasti, A. H., Sharpsten, L., & Medeiros, F. A. (2014) · Ophthalmology · doi:10.1016/j.ophtha.2014.01.015 · Cited by 12

Investigation of substrate specificity of wildtype and mutant BphKLB400 (a glutathione S-transferase) from Burkholderia LB400

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Statistical Evaluation of HTS Assays for Enzymatic Hydrolysis of β-Keto Esters

Buß, O., Jäger, S., Dold, S., Zimmermann, S., Hamacher, K., Schmitz, K., & Rudat, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0146104 · Cited by 12

Tabulations for value at risk and expected shortfall

Nadarajah, S., Chan, S., & Afuecheta, E. (2016) · Communication in Statistics- Theory and Methods · doi:10.1080/03610926.2015.1116572 · Cited by 12

Ligand-Based Methods in GPCR Computer-Aided Drug Design

Hawkins, P. C. D., & Stahl, G. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7465-8_18 · Cited by 12

The Early Years of Industrial and Organizational Psychology

Vinchur, A. J. (2018) · Cambridge University Press eBooks · doi:10.1017/9781107588608 · Cited by 12

Developments from analysis of variance through to generalized linear models and beyond

Payne, R. W. (2013) · Annals of Applied Biology · doi:10.1111/aab.12091 · Cited by 12

Isolation of folate-producing microalgae, from oligotrophic ponds in Yamaguchi, Japan

Fujii, K., Nakashima, H., & Hashidzume, Y. (2009) · Journal of Applied Microbiology · doi:10.1111/j.1365-2672.2009.04542.x · Cited by 12

The family and their close and distant relations

Jones, M. C. (2008) · Journal of the Korean Statistical Society · doi:10.1016/j.jkss.2008.06.002 · Cited by 12

The Statistical Education of Harold Jeffreys

Aldrich, J. (2006) · International Statistical Review · doi:10.1111/j.1751-5823.2005.tb00150.x · Cited by 12

Cross-over trials in drug development: theory and practice

Senn, S. J. (2001) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(00)00318-9 · Cited by 12

The influence of female presence and seasonality on the home range size and activity patterns of male domestic cats in Brazil’s Atlantic Forest

Ferreira, G. A., Nakano‐Oliveira, E., Andriolo, A., & Genaro, G. (2016) · Journal of Ethology · doi:10.1007/s10164-016-0466-8 · Cited by 12

Characterization of non-Gaussianity in gravitational wave detector noise

Yamamoto, T. S., Hayama, K., Mano, S., Itoh, Y., & Kanda, N. (2016) · Physical review. D/Physical review. D. · doi:10.1103/physrevd.93.082005 · Cited by 12

Microarrays

Zien, A., Fluck, J., Zimmer, R., & Lengauer, T. (2002) · doi:10.1145/565196.565239 · Cited by 12

Selective release of newly synthesized cardiac norepinephrine induced by angiotensin II

Chevillard, C., Duchène, N., & Alexandre, J.-M. (1971) · European Journal of Pharmacology · doi:10.1016/0014-2999(71)90071-9 · Cited by 12

Serum dopamine-beta-hydroxylase in depressed patients and the effect of electroconvulsive shock treatment

Lamprecht, F., Ebert, M. H., Turek, I., & Kopin, I. J. (1974) · Psychopharmacology · doi:10.1007/bf00429418 · Cited by 12

An introduction to modern statistical methods in HCI

Robertson, J., & Kaptein, M. (2016) · Human-computer interaction series · doi:10.1007/978-3-319-26633-6_1 · Cited by 8

Multipair phase-modulated temporal interference electrical stimulation combined with fMRI

Savvateev, I., Missey, F., Beliaeva, V., Peressotti, S., Markicevic, M., Kindler, D., Chaudun, F., Casarotto, G., Bellone, C., Lüscher, C., et al. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101610 · Cited by 15

Analysis of the influence of the type of heat transfer on the dynamics of the ignition processes of wood biomass particles under complex heating conditions

Кузнецов, Г. В., Syrodoy, S. V., Косторева, Ж. А., Nigay, N. A., Purin, M. V., Karelin, V. A., & Саломатов, В. В. (2024) · Combustion and Flame · doi:10.1016/j.combustflame.2024.113353 · Cited by 11

Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations

Betello, F., Siciliano, F., Mishra, P., & Silvestri, F. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56060-6_14 · Cited by 11

‘Are you even listening?’ - EEG-based decoding of absolute auditory attention to natural speech

Roebben, A., Heintz, N., Geirnaert, S., Francart, T., & Bertrand, A. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad5403 · Cited by 11

Seed Treatment with Cold Plasma and Electromagnetic Field: Changes in Antioxidant Capacity of Seedlings in Different Picea abies (L.) H. Karst Half-Sib Families

Čėsnienė, I., Čėsna, V., Miškelytė, D., Novickij, V., Mildažienė, V., & Sirgedaitė‐Šėžienė, V. (2024) · Plants · doi:10.3390/plants13152021 · Cited by 11

User Evaluation of a Shared Robot Control System Combining BCI and Eye Tracking in a Portable Augmented Reality User Interface

Dillen, A., Omidi, M., Ghaffari, F., Romain, O., Vanderborght, B., Roelands, B., Nowé, A., & Pauw, K. D. (2024) · Sensors · doi:10.3390/s24165253 · Cited by 11

Full-scale wind turbine performance assessment using the turbine performance integral (TPI) method: a study of aerodynamic degradation and operational influences

Malik, T. H., & Bak, C. (2024) · Wind energy science · doi:10.5194/wes-9-2017-2024 · Cited by 11

A Multi-Method Approach to Analyzing Precipitation Series and Their Change Points in Semi-Arid Climates: The Case of Dobrogea

Saliba, Y., & Bărbulescu, A. (2025) · Water · doi:10.3390/w17030391 · Cited by 11

Reproducibility of the Johns Hopkins Hospital template for urologic cytology samples

Olson, M. T., Novak, A., Boonyaarunnate, T., Trotter, J., Sachs, S., Kelly, D. P., Ford, S., Cornish, T. C., Toll, A. D., Tatsas, A. D., et al. (2014) · Journal of the American Society of Cytopathology · doi:10.1016/j.jasc.2014.02.003 · Cited by 11

Optimal Selection of Calibration and Validation Test Samples Under Uncertainty

Mullins, J., Li, C., Mahadevan, S., & Urbina, A. (2014) · Conference proceedings of the Society for Experimental Mechanics · doi:10.1007/978-3-319-04552-8_39 · Cited by 11

Künstliche Intelligenz und neuronale Netze in der Urologie

von Klot, C. A. J., & Kuczyk, M. A. (2018) · Der Urologe · doi:10.1007/s00120-018-0826-9 · Cited by 11

Obesity in Qatar: A Case-Control Study on the Identification of Associated Risk Factors

Khondaker, M. T. I., Khan, J. Y., Refaee, M. A., Hajj, N. E., Rahman, M. S., & Alam, T. (2020) · Diagnostics · doi:10.3390/diagnostics10110883 · Cited by 13

Recovering High‐Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation

Marcos, S., Parejo, M., Estonba, A., & Alberdi, A. (2022) · Advanced Genetics · doi:10.1002/ggn2.202100065 · Cited by 10

Regulator of G Protein Signaling Proteins Control Growth, Development and Cellulase Production in Neurospora crassa

Cabrera, I. E., Oza, Y., Carrillo, A. J., Collier, L. A., Wright, S. J., Li, L., & Borkovich, K. A. (2022) · Journal of Fungi · doi:10.3390/jof8101076 · Cited by 11

Duplication and neofunctionalization of a horizontally transferred xyloglucanase as a facet of the Red Queen coevolutionary dynamic

Attah, V., Milner, D. S., Fang, Y., Yan, X., Leonard, G., Heitman, J., Talbot, N. J., & Richards, T. A. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2218927121 · Cited by 11

Assessments about soil temperature variation under censored data and importance for geothermal energy applications. Illustration with Romanian data

Balan, M. C., Todoran, T. P., Bolboaca, S. D., & Jäntschi, L. (2013) · Journal of Renewable and Sustainable Energy · doi:10.1063/1.4812655 · Cited by 11

The millimeter-wavelength sulfur dioxide absorption spectra measured under simulated Venus conditions

Bellotti, A., & Steffes, P. G. (2015) · Icarus · doi:10.1016/j.icarus.2015.03.028 · Cited by 11

Multiple Coulomb scattering in thin silicon

Berger, N., Bunyatyan, A., Eckert, P., Förster, F. A., Gredig, R., Kovalenko, O., Kiehn, M., Philipp, R., Schöning, A., & Wiedner, D. (2014) · Journal of Instrumentation · doi:10.1088/1748-0221/9/07/p07007 · Cited by 11

On the Application of Inequality Indices in Comparative Software Analysis

Goloshchapova, O., & Lumpe, M. (2013) · Australasian Software Engineering Conference (ASWEC) · doi:10.1109/aswec.2013.23 · Cited by 11

Adjusting the Scott-Knott cluster analyses for unbalanced designs

Conrado, T. V., Ferreira, D. F., Scapim, C. A., Maluf, W. R., & UFLA, B. (2017) · Crop Breeding and Applied Biotechnology · doi:10.1590/1984-70332017v17n1a1 · Cited by 11

Benefits of the retail payments card market: Evidence from Russian merchants

Krivosheya, E., & Korolev, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2017.12.020 · Cited by 11

Essential phospholipids for people with non-alcoholic fatty liver disease

Varganova, D. L., Pavlov, C. S., Casazza, G., Nikolova, D., & Gluud, C. N. (2019) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013301 · Cited by 11

Room-temperature, atmospheric-pressure microsputtering of dense, electrically conductive, sub-100 nm gold films

Kornbluth, Y., Mathews, R. H., Parameswaran, L., Racz, L. M., & Velásquez–García, L. F. (2019) · Nanotechnology · doi:10.1088/1361-6528/ab1281 · Cited by 11

Variability in Consumption and End Uses of Water for Residential Users in Logan and Providence, Utah, US

Pacheco, C. J. B., Horsburgh, J. S., & Attallah, N. A. (2022) · Journal of Water Resources Planning and Management · doi:10.1061/(asce)wr.1943-5452.0001633 · Cited by 11

Basis of Geotechnical Design

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An Experimental Validation of Some Indexes of Fuzzy Clustering Similarity

Stefano Rovetta, A., & Masulli, F. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02282-1_17 · Cited by 11

Implementing Bayesian predictive procedures: The K-prime and K-square distributions

Poitevineau, J., & Lecoutre, B. (2008) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2008.11.004 · Cited by 11

W.S. Gosset and Some Neglected Concepts in Experimental Statistics: Guinnessometrics II

Ziliak, S. T. (2011) · Journal of Wine Economics · doi:10.1017/s1931436100001632 · Cited by 11

Statistics, probability, significance, likelihood: words mean what we define them to mean

Drummond, G. B., & Tom, B. D. M. (2011) · AJP Advances in Physiology Education · doi:10.1152/advan.00060.2011 · Cited by 11

Group composition and population density of rhesus monkey (Macaca mulatta (Zimmermann)) in northern India

Mukherjee, R. P., & Mukherjee, G. (1972) · Primates · doi:10.1007/bf01757937 · Cited by 11

NOVEL AND EXTENSIVE ASPECTS OF PARAQUAT-INDUCED PULMONARY FIBROGENESIS: COMPARATIVE AND TIME-COURSE MICROARRAY ANALYSES IN FIBROGENIC AND NON-FIBROGENIC RATS

SATOMI, Y., 坂口, 和., Kasahara, Y., & Akahori, F. (2007) · The Journal of Toxicological Sciences · doi:10.2131/jts.32.529 · Cited by 11

Using seismic crosswell surveys to determine the aperture of partially water-saturated fractures

Kaelin, B., & Johnson, L. R. (1999) · Geophysics · doi:10.1190/1.1444511 · Cited by 11

Greedy Ensemble Hyperspectral Anomaly Detection

Hossain, M., Younis, M., Robinson, A. L., Wang, L., & Preza, C. (2024) · Journal of Imaging · doi:10.3390/jimaging10060131 · Cited by 10

On Type 1 Active Galactic Nuclei with Double-peaked [O iii ]. I. Data Sample and Basic Results

Zheng, Q., Ma, Y., Zhang, X., Yuan, Q., & Bian, W. (2025) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/adb965 · Cited by 10

Low surface brightness structures from annotated deep CFHT images: effects of the host galaxy’s properties and environment

Sola, E., Duc, P., Urbano, M., Richards, F., Paiement, A., Bílek, M., Yıldız, M. K., Boselli, A., Côté, P., Cuillandre, J., et al. (2025) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/staf1139 · Cited by 10

Social priors to estimate relevance of a resource

Badache, I., & Boughanem, M. (2014) · Information Interaction in Context Symposium (IIiX) · doi:10.1145/2637002.2637016 · Cited by 10

Prediction of Nucleosome Positioning Based on Transcription Factor Binding Sites

Yi, X., Cai, Y., He, Z., Cui, W., & Kong, X. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012495 · Cited by 10

Adaptive Langevin Sampler for Separation of $t$-Distribution Modelled Astrophysical Maps

Kayabol, K., Kuruoğlu, E. E., Sanz, J. L., Sankur, B., Salerno, E., & Herranz, D. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2048613 · Cited by 10

View suggestion for interactive segmentation of indoor scenes

Yang, S. Y., Xu, J., Chen, K., & Fu, H. (2017) · Computational Visual Media · doi:10.1007/s41095-017-0078-4 · Cited by 10

Revisiting Statistical Design and Analysis in Scientific Research

Choi, K. R., Ryu, J. Y., & Lee, S. Y. (2018) · Small · doi:10.1002/smll.201802604 · Cited by 10

A need for a paradigm shift in focus: From Kt/V urea to appropriate removal of sodium (the ignored uremic toxin)

Twardowski, Z. J., & Misra, M. (2018) · Hemodialysis International · doi:10.1111/hdi.12701 · Cited by 10

Study of charmonium and charmonium-like contributions in B+ → J/ψηK+ decays

Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. A., Abudinén, F., Ackernley, T., Adeva, B., Adinolfi, M., Afsharnia, H., Agapopoulou, C., Aidala, C., et al. (2022) · Journal of High Energy Physics · doi:10.1007/jhep04(2022)046 · Cited by 18

Statistical Significance and Scientific Misconduct: Improving the Style of the Published Research Paper

Ziliak, S. T. (2016) · Review of Social Economy · doi:10.1080/00346764.2016.1150730 · Cited by 11

A rapid differential display analysis of nasal swab fingerprints to distinguish allergic from non‐allergic rhinitis subjects by mesoporous silica particles and MALDI‐TOF mass spectrometry

Lombardo, N., Preianò, M., Maggisano, G., Murfuni, M. S., Messina, L., Pelaia, G., Savino, R., & Terracciano, R. (2016) · PROTEOMICS · doi:10.1002/pmic.201600215 · Cited by 10

Transverse instability of ion acoustic solitons in a magnetized plasma including -nonextensive electrons and positrons

Akhtar, N., El‐Taibany, W. F., Mahmood, S., Behery, E. E., Khan, S. A., Ali, S., & Hussain, S. (2015) · Journal of Plasma Physics · doi:10.1017/s0022377815001038 · Cited by 10

Virtual Reality Using Smart-Devices in Educational Frameworks

Navarro, I., de Reina, O., Fonseca, D., Gómez, M., & Ferrer, Á. (2017) · International Journal of Technology and Human Interaction · doi:10.4018/ijthi.2017100104 · Cited by 10

The impact of age on number and distribution of proliferating cells in subgranular zone in adult mouse brain

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Side-channel Elimination via Partial Control-flow Linearization

Soares, L. D. C., Canesche, M., & Pereira, F. M. Q. (2023) · ACM Transactions on Programming Languages and Systems · doi:10.1145/3594736 · Cited by 10

The Bimodality Principle

Reschenhofer, E. (2001) · Journal of Statistics Education · doi:10.1080/10691898.2001.11910644 · Cited by 10

The exponential expansion of simulation in research

Powers, M. J., Sanchez, S. M., & Lucas, T. W. (2012) · Winter Simulation Conference · doi:10.1109/wsc.2012.6465125 · Cited by 10

Contributions of the passionate statistician

Grier, B., & Grier, M. R. (1978) · Research in Nursing & Health · doi:10.1002/nur.4770010303 · Cited by 10

The metabolism of amino‐acids by Paramecium caudatum

Emery, F. E. (1928) · Journal of Morphology · doi:10.1002/jmor.1050450207 · Cited by 10

An Alternative to Satterthwaite's Test Involving Positive Linear Combinations of Variance Components

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STATISTICAL COMPUTER METHODS FOR DIAGNOSIS

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Vergleichende experimentelle Untersuchungen �ber das Verhalten des Skeletmuskelgewebes der Albinomaus nach Infektion mit murinen Parapoliomyelitis-Viren, mausadaptierten und ?klassischen? Poliomyelitis-Viren

G�deke, R., Bayer, H., Hammel, B., Kanzler, S., & Sch�nberg, F. (1954) · Archives of Virology · doi:10.1007/bf01243002 · Cited by 10

Statistical Inference

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Evaluating the Effects of Sugar Shift® Symbiotic on Microbiome Composition and LPS Regulation: A Double-Blind, Placebo-Controlled Study

García, G., Soto, J., Netherland, M., Hasan, N. A., Faxas, E. B., Martínez, D., Carlin, M. R., & Cano, R. J. (2024) · Microorganisms · doi:10.3390/microorganisms12122525 · Cited by 11

Deep learning opportunistic screening for osteoporosis and osteopenia using radiographs of the foot or ankle – A pilot study

Gharehmohammadi, F., & Sebro, R. (2025) · European Journal of Radiology · doi:10.1016/j.ejrad.2025.111980 · Cited by 9

DiCS-Index: Predicting Student Performance in Computer Science by Analyzing Learning Behaviors

Capovilla, D., Hubwieser, P., & Shah, P. (2016) · International Conference on Learning and Teaching in Computing and Engineering (LaTICE) · doi:10.1109/latice.2016.12 · Cited by 9

An ensemble-based statistical methodology to detect differences in weather and climate model executables

Zeman, C., & Schär, C. (2022) · Geoscientific model development · doi:10.5194/gmd-15-3183-2022 · Cited by 12

Fitting Bell Curves to Data Distributions Using Visualization

Newburger, E., Correll, M., & Elmqvist, N. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3210763 · Cited by 9

Exploring the implicit interlayer regulatory mechanism between cells and tissue: Stochastic mathematical analyses of the spontaneous ordering in beating synchronization

Hamada, H., Nomura, F., Kaneko, T., Yasuda, K., & Okamoto, M. (2013) · Biosystems · doi:10.1016/j.biosystems.2013.02.007 · Cited by 9

Time-resolved biomarker discovery in 1H-NMR data using generalized fuzzy Hough transform alignment and parallel factor analysis

Alm, E., Torgrip, R. J. O., Åberg, K. M., Schuppe‐Koistinen, I., & Lindberg, J. (2010) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-009-3421-5 · Cited by 9

Traceability Challenge 2013: Statistical analysis for traceability experiments: Software verification and validation research laboratory (SVVRL) of the University of Kentucky

Hays, M., Hayes, J. H., Stromberg, A. J., & Bathke, A. C. (2013) · International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE) · doi:10.1109/tefse.2013.6620161 · Cited by 9

UDP-galactose 4′-epimerase from the liver fluke,Fasciola hepatica: biochemical characterization of the enzyme and identification of inhibitors

Zinsser, V. L., Lindert, S., Banford, S., Hoey, E. M., Trudgett, A., & Timson, D. J. (2014) · Parasitology · doi:10.1017/s003118201400136x · Cited by 9

Experimental study of the effect of drift angle on a ship-like foil with varying aspect ratio and bottom edge shape

Kramer, J. V., Steen, S., & Savio, L. (2016) · Ocean Engineering · doi:10.1016/j.oceaneng.2016.06.004 · Cited by 9

An Analysis of the Links between Smoking and BMI in Adolescents: A Moving Average Approach to Establishing the Statistical Relationship between Quantitative and Dichotomous Variables

Вараксин, А. Н., Даниловна, К. Е., Maslakova, T. A., Shalaumova, Y. V., & Nasybullina, G. M. (2022) · Children · doi:10.3390/children9020220 · Cited by 9

Delayed processing of blood samples impairs the accuracy of mRNA-based biomarkers

Wilson, C., Dias, N. W. W., Pancini, S., Mercadante, V. R. G., & Biase, F. H. (2022) · Scientific Reports · doi:10.1038/s41598-022-12178-5 · Cited by 9

A Biomedical Case Study Showing That Tuning Random Forests Can Fundamentally Change the Interpretation of Supervised Data Structure Exploration Aimed at Knowledge Discovery

Lötsch, J., & Mayer, B. (2022) · BioMedInformatics · doi:10.3390/biomedinformatics2040034 · Cited by 9

Tsunami risk perception in central and southern Italy

Cugliari, L., Crescimbene, M., Longa, F. L., Cerase, A., Amato, A., & Cerbara, L. (2022) · Natural hazards and earth system sciences · doi:10.5194/nhess-22-4119-2022 · Cited by 9

SEDIMENTATION FIELD-FLOW FRACTIONATION AS A TOOL FOR THE STUDY OF MILK PROTEIN-STABILIZED MODEL OIL-IN-WATER EMULSIONS: EFFECT OF PROTEIN CONCENTRATION AND HOMOGENIZATION PRESSURE

Κέντα, Σ., Raikos, V., Kapolos, J., Koliadima, A., & Karaiskakis, G. (2013) · Journal of Liquid Chromatography & Related Technologies · doi:10.1080/10826076.2011.653853 · Cited by 9

Optimal estimator for uncertainty-based measurement quality control

Huang, H. (2015) · Accreditation and Quality Assurance · doi:10.1007/s00769-015-1111-x · Cited by 9

3.6 GHz highly monotonic digitally controlled oscillator for all-digital phase locked loop

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Phlebiopsis gigantea and associated viruses survive passing through the digestive tract of Hylobius abietis

Drenkhan, T., Kasanen, R., & Vainio, E. J. (2015) · Biocontrol Science and Technology · doi:10.1080/09583157.2015.1111998 · Cited by 9

An improved numerical optimization method for efficient beam search in 60 GHz indoor millimeter wave wireless networks

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Forecasting Nigeria’s inflation and the world prices of her major agricultural export commodities with probability distributions via VaR and ES and estimating their dependence via copula

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Analysis of Fermi-LAT data from Tucana-II: possible constraints on the Dark Matter models with an intriguing hint of a signal

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Design and implementation of S-MARKS: A secure middleware for pervasive computing applications

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Comparison of Methods for Degassing Beer for Analysis

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CHEMICAL CHANGES INDUCED IN POTATO TUBERS BY TREATMENTS THAT BREAK THE REST PERIOD

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Ascorbic Acid and Epithelial Regeneration

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Inhibition of cholesterol synthesis in mammary tissue, lung, and kidney following cholesterol feeding in the lactating rat

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On the Probable Error of Mean-Square Contingency

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ON THE PROBABLE ERROR OF BISERIAL

Pearson, K. (1917) · Biometrika · doi:10.1093/biomet/11.4.292

The Law of Error.

E., W. P., Edgeworth, F. Y., & Charlier, C. V. L. (1906) · Biometrika · doi:10.2307/2331663 · Cited by 2

TABLES FOR FACILITATING THE COMPUTATION OF PROBABLE ERRORS

GIBSON, W. (1906) · Biometrika · doi:10.1093/biomet/4.4.385 · Cited by 2

On Certain Points Concerning the Probable Error of the Standard Deviation

Pearl, R. (1908) · Biometrika · doi:10.2307/2331564 · Cited by 1