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As per available reports about 8 relevant Journal more than 10 Conferences and 52 Conferences Proceedings are presently dedicated exclusively to Statistical methods and about 8 Open Access articles are being published on Statistical methods.
Statistical methods are the methods of collecting, summarizing, analysing, and interpreting variable numerical data. Statistical methods can be contrasted with deterministic methods, which are appropriate where observations are exactly reproducible or are assumed to be so. While statistical methods are widely used in the life sciences, in economics, and in agricultural science, they also have an important role in the physical sciences in the study of measurement errors, of random phenomena such as radioactivity or meteorological events, and in obtaining approximate results where deterministic solutions are hard to apply. Data collection involves deciding what to observe in order to obtain information relevant to the questions whose answers are required, and then making the observations. Sampling involves choice of a sufficient number of observations representing an appropriate population. Experiments with variable outcomes should be conducted according to principles of experimental design. Topics like: Text Processing, Computational complexity, Documents with High Dimensions are of interested.
OMICS International Organizes 1000+ Global Events Every Year across USA, Europe & Asia with support from 1000 more scientific societies and Publishes 700+ Open access journals which contains over 100000 eminent personalities, reputed scientists as editorial board and organizing committee members. The conference series website will provide you list and details about the conference organize worldwide.
Scope & Importance:
Data summarization is the calculation of appropriate statistics and the display of such information in the form of tables, graphs, or charts. Data may also be adjusted to make different samples more comparable, using ratios, compensating factors, etc. Statistical analysis relates observed statistical data to theoretical models, such as probability distributions or models used in regression analysis. By estimating parameters in the proposed model and testing hypotheses about rival models, one can assess the value of the information collected and the extent to which the information can be applied to similar situations. Statistical prediction is the application of the model thought to be most appropriate, using the estimated values of the parameters.
Statistical Methods conference aims at bringing together researchers and practitioners to discuss recent developments in statistical methods, computational methods, methodologies for data analysis and applications in statistics.
The data acquired for quantitative marketing research can be analysed by almost any of the range of techniques of statistical analysis, which can be broadly divided into descriptive statistics and statistical inference. An important set of techniques is that related to statistical surveys. In any instance, an appropriate type of statistical analysis should take account of the various types of error that may arise, as outlined below. Reliability is the extent to which a measure will produce consistent results. Test-retest reliability checks how similar the results are if the research is repeated under similar circumstances. Stability over repeated measures is assessed with the Pearson coefficient. Alternative forms reliability checks how similar the results are if the research is repeated using different forms. Internal consistency reliability checks how well the individual measures included in the research are converted into a composite measure. Internal consistency may be assessed by correlating performance on two halves of a test (split-half reliability).
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This page was last updated on 12th Sep, 2015
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