The Probable Error of a Mean

Application of Artificial Intelligent in the Prediction of Consumer Behavior from Facebook Posts Analysis

Kachamas, P., Akkaradamrongrat, S., Sinthupinyo, S., & Chandrachai, A. (2019) · International Journal of Machine Learning and Computing · doi:10.18178/ijmlc.2019.9.1.770 · Cited by 23

Effect of Fibrin Concentration on the In Vitro Production of Dermo-Epidermal Equivalents

Montero, A., Quílez, C., Valencia, L., Girón, P., Jorcano, J. L., & Velasco, D. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22136746 · Cited by 23

An ancient route towards salicylic acid and its implications for the perpetual Trichormus–Azolla symbiosis

de Vries, S., Herrfurth, C., Li, F., Feußner, I., & de Vries, J. (2023) · Plant Cell & Environment · doi:10.1111/pce.14659 · Cited by 23

XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning

Zöller, M.-A., Titov, W., Schlegel, T., & Huber, M. F. (2023) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3625240 · Cited by 38

Elevated curdlan production by a mutant of Agrobacterium sp. ATCC 31749

West, T. P. (2009) · Journal of Basic Microbiology · doi:10.1002/jobm.200900137 · Cited by 23

Middle East Respiratory Syndrome Coronavirus in Dromedaries in Ethiopia Is Antigenically Different From the Middle East Isolate EMC

Shirato, K., Melaku, S. K., Kawachi, K., Nao, N., Iwata‐Yoshikawa, N., Kawase, M., Kamitani, W., Matsuyama, S., Tessema, T. S., & Sentsui, H. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.01326 · Cited by 23

Predicting software defect type using concept-based classification

Patil, S., & Ravindran, B. (2020) · Empirical Software Engineering · doi:10.1007/s10664-019-09779-6 · Cited by 27

`Student' and Small Sample Theory

Welch, B. L. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501478 · Cited by 23

Information Processing: The Language and Analytical Tools for Cognitive Psychology in the Information Age

Xiong, A., & Proctor, R. W. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01270 · Cited by 29

Changes Occurring in the Proteins as a Result of Processing Groundnuts under Selected Industrial Conditions

Cama, H. R., & Morton, R. A. (1950) · British Journal Of Nutrition · doi:10.1079/bjn19500055 · Cited by 23

Inhalation toxicology of sodium sulfite aerosols in rats

Last, J. A., Dasgupta, P. Κ., & Etchison, J. R. (1980) · Toxicology and Applied Pharmacology · doi:10.1016/0041-008x(80)90084-8 · Cited by 23

The t‐distribution and its relationship to the normal distribution

Brereton, R. G. (2015) · Journal of Chemometrics · doi:10.1002/cem.2713 · Cited by 22

Analyzing Brain Waves of Table Tennis Players with Machine Learning for Stress Classification

Tsai, Y.-H., Wu, S.-K., Yu, S.-S., & Tsai, M.-H. (2022) · Applied Sciences · doi:10.3390/app12168052 · Cited by 25

Philosophy of Econometrics

Spanos, A. (2012) · Elsevier eBooks · doi:10.1016/b978-0-444-51676-3.50013-0 · Cited by 22

Artemisinins act through at least two targets in a yeast model

Moore, C. M., Hoey, E. M., Trudgett, A., & Timson, D. J. (2010) · FEMS Yeast Research · doi:10.1111/j.1567-1364.2010.00706.x · Cited by 24

Dynamic unmagnetized plasma in the diamagnetic cavity around comet 67P/Churyumov–Gerasimenko

Hajra, R., Henri, P., Vallières, X., Moré, J., Gilet, N., Wattieaux, G., Goetz, C., Richter, I., Tsurutani, B. T., Gunell, H., et al. (2018) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/sty094 · Cited by 22

Effects of force fields on the conformational and dynamic properties of amyloid β(1‐40) dimer explored by replica exchange molecular dynamics simulations

Watts, C. R., Gregory, A., Frisbie, C. P., & Lovas, S. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25439 · Cited by 22

Harmonization of diffusion MRI data sets with adaptive dictionary learning

St‐Jean, S., Viergever, M. A., & Leemans, A. (2020) · Human Brain Mapping · doi:10.1002/hbm.25117 · Cited by 21

History of the Statistical Design of Agricultural Experiments

Verdooren, L. R. (2020) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-020-00394-3 · Cited by 22

Frequency analysis and its spatiotemporal characteristics of precipitation extreme events in China during 1951–2010

Shao, Y., Wu, J., Ye, J., & Liu, Y. (2015) · Theoretical and Applied Climatology · doi:10.1007/s00704-015-1481-3 · Cited by 22

Typologies in GPs’ referral practice

Thorsen, O., Hartveit, M., Johannessen, J. O., Fosse, L., Eide, G. E., Schulz, J., & Bærheim, A. (2016) · BMC Family Practice · doi:10.1186/s12875-016-0495-y · Cited by 22

The morphology of landscape elements as predictors of water quality in glacial/boreal lakes

Thierfelder, T. (1998) · Journal of Hydrology · doi:10.1016/s0022-1694(98)00134-6 · Cited by 22

Cardiovascular dynamics during coronary sinus, right atrial, and right ventricular pacing

Befeler, B., Hildner, F. J., Javier, R. P., Cohen, L. S., & D, P. S. M. (1971) · American Heart Journal · doi:10.1016/0002-8703(71)90107-4 · Cited by 22

Fisher's Z ‐Transformation

Mudholkar, G. S. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess0796.pub2 · Cited by 22

Chemotherapy of Experimental Schistosomiasis Mansoni: Prophylactic and Protective Activity of Clinically Active Compounds in Mice and Hamsters

Stohler, H. R., & Frey, J. R. (1963) · Annals of Tropical Medicine and Parasitology · doi:10.1080/00034983.1963.11686202 · Cited by 22

Non-invasive positive pressure ventilation for acute asthma in children

Korang, S. K., Feinberg, J. B., Wetterslev, J., & Jakobsen, J. C. (2016) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd012067 · Cited by 22

Person-Centered Learning using Peer Review Method – An Evaluation and a Concept for Student-Centered Classrooms

Dolezal, D., Posekany, A., Roschger, C., Koppensteiner, G., Motschnig, R., & Pucher, R. (2018) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v8i1.8099 · Cited by 22

Radiomics-Based Classification of Tumor and Healthy Liver on Computed Tomography Images

Zossou, V.-B. S., Gnangnon, F. H. R., Biaou, O., de Vathaire, F., Allodji, R. S., & Ezin, E. C. (2024) · Cancers · doi:10.3390/cancers16061158 · Cited by 22

Least-squares two-sample test

Sugiyama, M., Suzuki, T., Itoh, Y., Kanamori, T., & Kimura, M. (2011) · Neural Networks · doi:10.1016/j.neunet.2011.04.003 · Cited by 21

X-ray diffraction reveals the intrinsic difference in the physical properties of membrane and soluble proteins

Robert, X., Kassis-Sahyoun, J., Ceres, N., Martin, J., Sawaya, M. R., Read, R. J., Gouet, P., Falson, P., & Chaptal, V. (2017) · Scientific Reports · doi:10.1038/s41598-017-17216-1 · Cited by 21

Alchemical Free-Energy Calculations by Multiple-Replica λ-Dynamics: The Conveyor Belt Thermodynamic Integration Scheme

Hahn, D. F., & Hünenberger, P. H. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00782 · Cited by 21

Automatic tuning via Kriging-based optimization of methods for fault detection and isolation

Marzat, J., Walter, E., Piet-Lahanier, H., & Damongeot, F. (2010) · Conference on Control and Fault-Tolerant Systems · doi:10.1109/systol.2010.5676075 · Cited by 21

A comparison of fuzzy strategies for corporate acquisition analysis

Glackin, C., Maguire, L., McIvor, R., Humphreys, P. K., & Herman, P. A. (2007) · Fuzzy Sets and Systems · doi:10.1016/j.fss.2007.03.020 · Cited by 21

Adaptive Local Learning Soft Sensor for Inferential Control Support

Kadlec, P., & Gabryś, B. (2008) · Computational Intelligence for Modelling, Control and Automation · doi:10.1109/cimca.2008.66 · Cited by 21

East Asian wisdom and relativity

Baumann, C., Winzar, H. F., & Fang, T. (2018) · Cross Cultural & Strategic Management · doi:10.1108/ccsm-01-2018-0007 · Cited by 23

Stiffness of dowel-type timber connections under pre-yield oscillating loads

Reynolds, T., Harris, R., & Chang, W. (2014) · Engineering Structures · doi:10.1016/j.engstruct.2014.01.024 · Cited by 21

Confidence intervals based on one or more observations

Blachman, N. M., & Machol, R. E. (1987) · IEEE Transactions on Information Theory · doi:10.1109/tit.1987.1057306 · Cited by 21

Improving vision-based obstacle detection on USV using inertial sensor

Bovcon, B., Mandeljc, R., Perš, J., & Kristan, M. (2017) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2017.8073559 · Cited by 21

Enhancing Control Room Operator Decision Making

Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Baldissone, G., Madsen, A. L., Demichela, M., & Leva, M. C. (2024) · Processes · doi:10.3390/pr12020328 · Cited by 20

Rank-Biased Precision Reloaded: Reproducibility and Generalization

Ferro, N., & Silvello, G. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16354-3_83 · Cited by 20

Alternatives to statistical decision trees in regulatory (eco-)toxicological bioassays

Kluxen, F. M., & Hothorn, L. A. (2020) · Archives of Toxicology · doi:10.1007/s00204-020-02690-w · Cited by 21

Handling Heterogeneity in Programming Courses for Freshmen

Capovilla, D., Berges, M., Mühling, A., & Hubwieser, P. (2015) · International Conference on Learning and Teaching in Computing and Engineering (LaTICE) · doi:10.1109/latice.2015.18 · Cited by 20

The Guanine Nucleotide Exchange Factor RIC8 Regulates Conidial Germination through Gα Proteins in Neurospora crassa

Eaton, C. J., Cabrera, I. E., Servin, J. A., Wright, S. J., Cox, M. P., & Borkovich, K. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048026 · Cited by 20

Raced profiles

Leather, H., O’boyle, M. F. P., & Worton, B. J. (2009) · ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES) · doi:10.1145/1542452.1542460 · Cited by 20

A personal history of sensory science

Heymann, H. (2019) · Food Culture & Society · doi:10.1080/15528014.2019.1573043 · Cited by 20

A Probabilistic Proof of Wallis's Formula for π

Miller, S. J. (2008) · American Mathematical Monthly · doi:10.1080/00029890.2008.11920586 · Cited by 20

Defining the combinatorial space of PKC::CARD‐CC signal transduction nodes

Staal, J., Driege, Y., Haegman, M., Kreike, M., Iliaki, S., Vanneste, D., Lork, M., Afonina, I. S., Braun, H., & Beyaert, R. (2020) · FEBS Journal · doi:10.1111/febs.15522 · Cited by 20

Testing statistical hypotheses: the story of a book

Lehmann, E. L. (1997) · Statistical Science · doi:10.1214/ss/1029963261 · Cited by 20

Chemical proteomic and bioinformatic strategies for the identification and quantification of vascular antigens in cancer

Strassberger, V., Fugmann, T., Neri, D., & Roesli, C. (2010) · Journal of Proteomics · doi:10.1016/j.jprot.2010.05.018 · Cited by 21

The use of sedimentation field-flow fractionation in the size characterization of bovine milk fat globules as affected by heat treatment

Raikos, V., Kapolos, J., Farmakis, L., Koliadima, A., & Karaiskakis, G. (2009) · Food Research International · doi:10.1016/j.foodres.2009.02.001 · Cited by 20

The Passage of Vitamin A from Mother to Young in the Rat

Henry, K. M., Kon, S. K., Mawson, E. H., Stanier, J. E., & Thompson, S. Y. (1949) · British Journal Of Nutrition · doi:10.1079/bjn19490045 · Cited by 20

Composition―Nanostructure Steered Performance Predictions in Steel Wires

Tian, K. V., Passaretti, F., Nespoli, A., Placidi, E., Condò, R., Andreani, C., Licoccia, S., Chass, G. A., Senesi, R., & Cozza, P. (2019) · Nanomaterials · doi:10.3390/nano9081119 · Cited by 19

Sex Work during the 2010 FIFA World Cup: Results from a Three-Wave Cross-Sectional Survey

Delva, W., Richter, M. L., Koker, P. D., Chersich, M., & Temmerman, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028363 · Cited by 19

Traumatic spinal cord injury among children and adolescents; a cohort study in western Norway

Hagen, E. M., Eide, G. E., & Elgen, I. B. (2011) · Spinal Cord · doi:10.1038/sc.2011.42 · Cited by 19

Towards exploratory hypothesis testing and analysis

Liu, G., Feng, M., Wang, Y., Wong, L., Ng, S.-K., Mah, T. L., & Lee, E. J. D. (2011) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2011.5767907 · Cited by 19

Retrieval of aerosol optical depth in the visible range with a Brewer spectrophotometer in Athens

Diémoz, H., Eleftheratos, K., Kazadzis, S., Amiridis, V., & Zerefos, C. (2016) · Atmospheric measurement techniques · doi:10.5194/amt-9-1871-2016 · Cited by 19

Exploring the selectivity of WO 3 with iridium catalyst in an ethanol/naphthalene mixture using multivariate statistics

Bastuck, M., Puglisi, D., Huotari, J., Sauerwald, T., Lappalainen, J., Spetz, A. L., Andersson, M., & Schütze, A. (2016) · Thin Solid Films · doi:10.1016/j.tsf.2016.08.002 · Cited by 19

Terahertz Imaging and Electromagnetic Model of Axon Demyelination in Alzheimer's Disease

Yeo, W., Gurel, O., Srinivasan, N., King, P. D., Nahar, N. K., Park, S., Lehman, N. L., & Sertel, K. (2017) · IEEE Transactions on Terahertz Science and Technology · doi:10.1109/tthz.2017.2739481 · Cited by 19

Utilisation of GlutoPeak tester on whole-wheat flour for gluten quality assessment

Karaduman, Y., Önder, O., Sayaslan, A., & Aydın, N. (2019) · Quality Assurance and Safety of Crops & Foods · doi:10.3920/qas2018.1319 · Cited by 19

Statistical Pattern Recognition and Machine Learning in Brain–Computer Interfaces

Rao, R. P. N., & Scherer, R. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-375027-3.00010-7 · Cited by 21

The Proper Fiducial Argument

Hampel, F. R. (2006) · Lecture notes in computer science · doi:10.1007/11889342_29 · Cited by 19

De novo CDP‐choline‐dependent glycerophosphorylcholine synthesis and its involvement as an intermediate in phosphatidylcholine synthesis

Infante, J. P. (1987) · FEBS Letters · doi:10.1016/0014-5793(87)80031-5 · Cited by 19

Evaluation of earthquake stochastic models based on their real-time forecasts: a case study of Kaikoura 2016

Harte, D. S. (2019) · Geophysical Journal International · doi:10.1093/gji/ggz088 · Cited by 18

Simulated Dryland Cotton Yield Response to Selected Scenario Factors Associated With Soil Health

Ale, S., Himanshu, S. K., Mauget, S. A., Hudson, D., Goebel, T. S., Liu, B., Baumhardt, R. L., Bordovsky, J. P., Bräuer, D., Lascano, R. J., et al. (2021) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2020.617509 · Cited by 18

StainCUT: Stain Normalization with Contrastive Learning

Pérez, J. C. G., Baguer, D. O., & Maaß, P. (2022) · Journal of Imaging · doi:10.3390/jimaging8070202 · Cited by 18

Classification of BCI-EEG Based on the Augmented Covariance Matrix

Carrara, I., & Papadopoulo, T. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3386219 · Cited by 18

A NOVEL INHIBITOR OF VACUOLAR ATPase, FR202126, PREVENTS ALVEOLAR BONE DESTRUCTION IN EXPERIMENTAL PERIODONTITIS IN RATS

Niikura, K., Takeshita, N., & Chida, N. (2005) · The Journal of Toxicological Sciences · doi:10.2131/jts.30.297 · Cited by 18

GARCH modeling of five popular commodities

Nadarajah, S., Afuecheta, E., & Chan, S. (2014) · Empirical Economics · doi:10.1007/s00181-014-0845-3 · Cited by 18

Significance Testing Needs a Taxonomy

Bradley, M. T., & Brand, A. (2016) · Psychological Reports · doi:10.1177/0033294116662659 · Cited by 14

On Discrete Poisson-Shanker Distribution and Its Applications

Shanker, R. (2017) · Biometrics & Biostatistics International Journal · doi:10.15406/bbij.2017.05.00121 · Cited by 18

Reevaluation of the Acute Cystitis Symptom Score, a Self-Reporting Questionnaire. Part II. Patient-Reported Outcome Assessment

Alidjanov, J. F., Naber, K. G., Abdufattaev, U. A., Pilatz, A. M. E., & Wagenlehner, F. R. A. (2018) · Antibiotics · doi:10.3390/antibiotics7020043 · Cited by 18

Luke: An autonomous robot photographer

Zabarauskas, M., & Cameron, S. (2014) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2014.6907096 · Cited by 18

Glucocorticoid regulation of rat liver urate oxidase

Raab, L. S., Decker, G. L., Jonas, A. J., Kaetzel, M. A., & Dedman, J. R. (1991) · Journal of Cellular Biochemistry · doi:10.1002/jcb.240470104 · Cited by 18

On the lack of a radio afterglow from some gamma-ray bursts – insight into their progenitors?

Lloyd-Ronning, N., & Fryer, C. L. (2017) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stx313 · Cited by 18

Instrument design and protocol for the study of light controlled processes in aquatic organisms, and its application to examine the effect of infrared light on zebrafish

Dekens, M. P. S., Foulkes, N. S., & Tessmar‐Raible, K. (2017) · PLoS ONE · doi:10.1371/journal.pone.0172038 · Cited by 18

Organ: Body‐weight ratios for certain organs of laboratory animals. III. White Swiss mouse

Webster, S. H., & Liljegren, E. J. (1955) · American Journal of Anatomy · doi:10.1002/aja.1000970105 · Cited by 18

R. A. Fisher and the last fifty years of statistical methodology

Bartlett, M. S. (1975) · Springer eBooks · doi:10.1007/978-94-009-5889-0_2 · Cited by 18

A Statistical Analysis of CryptocurrenciesPreprint

Osterrieder, J. R., Chan, S., Chu, J., & Nadarajah, S. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2948315 · Cited by 18

Bisphenol A analysis and quantification inconsistencies via HPLC-UV: a systematic review with technical notes

Pop, C.-E., Miu, B. A., Németh, D., Wolff, R., Mihailescu, D. F., Avramescu, S. M., & Mernea, M. (2024) · Discover Applied Sciences · doi:10.1007/s42452-023-05617-z · Cited by 24

Significance of uncertain phasing between the onsets of stadial–interstadial transitions in different Greenland ice core proxies

Riechers, K., & Boers, N. (2021) · Climate of the past · doi:10.5194/cp-17-1751-2021 · Cited by 17

Distinguishing short and longFermigamma-ray bursts

Tarnopolski, M. (2015) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stv2061 · Cited by 17

Quantitative arterial spin labelling perfusion measurements in rat models of renal transplantation and acute kidney injury at 3 T

Zimmer, F., Klotz, S., Hoeger, S., Yard, B. A., Krämer, B. K., Schad, L. R., & Zöllner, F. G. (2016) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2016.02.004 · Cited by 17

Fresh and Diverse Social Signals

Badache, I., & Boughanem, M. (2017) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3020165.3020177 · Cited by 17

The wavelet transform as a Gaussian process for damage detection

Balafas, K., Kiremidjian, A. S., & Rajagopal, R. (2017) · Structural Control and Health Monitoring · doi:10.1002/stc.2087 · Cited by 17

The Hot Spot in a Cold Environment: Puzzling Parvodinium (Peridiniopsidaceae, Peridiniales) from the Polish Tatra Mountains

Kretschmann, J., Owsianny, P. M., Čalasan, A. Ž., & Gottschling, M. (2018) · Protist · doi:10.1016/j.protis.2018.02.004 · Cited by 17

Visualizing balances of compositional data: A new alternative to balance dendrograms

Quinn, T. P. (2018) · F1000Research · doi:10.12688/f1000research.15858.1 · Cited by 16

Using Statistics to Assess Lethal Violence in Civil and Inter-State War

Ball, P., & Price, M. (2018) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-030718-105222 · Cited by 17

Temporal ordering of omics and multiomic events inferred from time-series data

Kaur, S., Peters, T. J., Yang, P., Luu, L. D. W., Vuong, J., Krycer, J. R., & O’Donoghue, S. I. (2020) · npj Systems Biology and Applications · doi:10.1038/s41540-020-0141-0 · Cited by 15

The compositional organization and the expression of the Arabidopsis genome

Carels, N., & Bernardi, G. (2000) · FEBS Letters · doi:10.1016/s0014-5793(00)01476-9 · Cited by 17

Absence of liver tumor-initiating activity of kojic acid in mice

Moto, M., Mori, T., Okamura, M., Kashida, Y., & Mitsumori, K. (2005) · Archives of Toxicology · doi:10.1007/s00204-005-0034-4 · Cited by 17

Robustness and power of parametric, nonparametric, robustified and adaptive tests—The multi-sample location problem

Büning, H. (2000) · Statistical Papers · doi:10.1007/bf02925759 · Cited by 17

Mathematical modeling for the prediction of cerebral white matter lesions based on clinical examination data

Shinkawa, Y., Yoshida, T., Onaka, Y., Ichinose, M., & Ishii, K. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215142 · Cited by 18

A comparative study of oat (Avena sativa) cultivars as brewing adjuncts

Schnitzenbaumer, B., & Arendt, E. K. (2013) · European Food Research and Technology · doi:10.1007/s00217-013-1965-2 · Cited by 17

Soft tissue sarcomas of the popliteal fossa: Outcome and risk factors

Rüdiger, H. A., Beltrami, G., Campanacci, D. A., Mela, M. M., Franchi, A., & Capanna, R. (2006) · European Journal of Surgical Oncology · doi:10.1016/j.ejso.2006.11.009 · Cited by 17

Playing Safe with Misweighted Means

Cressie, N. (1982) · Journal of the American Statistical Association · doi:10.1080/01621459.1982.10477882 · Cited by 17

A classified bibliography of Monte Carlo studies in econometrics

SOWEY, E. R. (1973) · Journal of Econometrics · doi:10.1016/0304-4076(73)90023-7 · Cited by 17

Factors affecting the stability and estimation of carotene in artificially dried grass and hays

Kon, S. K., & Thompson, S. Y. (1940) · The Journal of Agricultural Science · doi:10.1017/s0021859600048267 · Cited by 17

T-Test with Likert Scale VariablesPreprint

Vieira, P. C. C. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2770035 · Cited by 17

Effects of Resolution, Cumulus Parameterization Scheme, and Probability Forecasting on Precipitation Forecasts in a High-Resolution Limited-Area Ensemble Prediction System

On, N., Kim, H. M., & Kim, S. (2018) · Asia-Pacific Journal of Atmospheric Sciences · doi:10.1007/s13143-018-0081-4 · Cited by 16

Freshwater Fish Siberian Dace Ingest Microplastics in the Remote Yenisei Tributary

Frank, Y. A., Vorobiev, D. S., Mandal, A., Lemeshko, Y., Rakhmatullina, S. N., & Darbha, G. K. (2022) · Toxics · doi:10.3390/toxics11010038 · Cited by 16

On the Probable Error of Mean-Square Contingency

BLAKEMAN, J., & Pearson, K. (1906) · Biometrika · doi:10.2307/2331660 · Cited by 2

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