Topic
Data analysis
About: Data analysis is a research topic. Over the lifetime, 6124 publications have been published within this topic receiving 181304 citations. The topic is also known as: multidimensional descriptive analysis.
Papers published on a yearly basis
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Papers
Book•
3 Mar 1992TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.
Abstract: Introduction The Logic of Hierarchical Linear Models Principles of Estimation and Hypothesis Testing for Hierarchical Linear Models An Illustration Applications in Organizational Research Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known Three-Level Models Assessing the Adequacy of Hierarchical Models Technical Appendix
24,451 citations
TL;DR: This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.
19,489 citations
Book•
3 Feb 1984
TL;DR: This paper presents the results of a series of experiments conducted in farmers' fields in the Czech Republic over a period of three years to investigate the effects of agricultural pesticides on animal welfare and human health.
Abstract: Elements of Experimentation. Single-Factor Experiments. Two-Factor Experiments. Three-or More-Factor Experiments. Comparison Between Treatment Means. Analysis of Multiobservation Data. Problem Data. Analysis of Data from a Series of Experiments. Regression and Correlation Analysis. Covariance Analysis. Chi-Square Test. Soil Heterogeneity. Competition Effects. Mechanical Errors. Sampling in Experimental Plots. Experiments in Farmers' Fields. Presentation of Experimental Results. Appendices. Index.
18,266 citations
TL;DR: In this paper, Hierarchical Linear Models: Applications and Data Analysis Methods are used for data analysis in the context of statistical data analysis, and the authors propose a hierarchical linear model.
Abstract: (2003). Hierarchical Linear Models: Applications and Data Analysis Methods. Journal of the American Statistical Association: Vol. 98, No. 463, pp. 767-768.
12,826 citations
Book•
1 Jan 1973
TL;DR: In this article, a thoroughly revised edition presents important methods in the quantitative analysis of geologic data, such as probability, nonparametric statistics, and Fourier analysis, as well as data analysis methods such as the semivariogram and the process of kriging.
Abstract: From the Publisher:
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
6,761 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 280 |
| 2024 | 435 |
| 2023 | 373 |
| 2022 | 486 |
| 2021 | 496 |
| 2020 | 610 |