This dataset is about book subjects and is filtered where the books includes Applied statistics. It has 10 columns such as book subject, earliest publication date, latest publication date, average publication date, and number of authors. The data is ordered by earliest publication date (descending).

Esto es una prueba

dataset and Octave/MatLab codes/scripts for data analysis Background: Methods for p-value correction are criticized for either increasing Type II error or improperly reducing Type I error. This problem is worse when dealing with thousands or even hundreds of paired comparisons between waves or images which are performed point-to-point. This text considers patterns in probability vectors resulting from multiple point-to-point comparisons between two event-related potentials (ERP) waves (mass univariate analysis) to correct p-values, where clusters of signiticant p-values may indicate true H0 rejection. New method: We used ERP data from normal subjects and other ones with attention deficit hyperactivity disorder (ADHD) under a cued forced two-choice test to study attention. The decimal logarithm of the p-vector (p') was convolved with a Gaussian window whose length was set as the shortest lag above which autocorrelation of each ERP wave may be assumed to have vanished. To verify the reliability of the present correction method, we realized Monte-Carlo simulations (MC) to (1) evaluate confidence intervals of rejected and non-rejected areas of our data, (2) to evaluate differences between corrected and uncorrected p-vectors or simulated ones in terms of distribution of significant p-values, and (3) to empirically verify rate of type-I error (comparing 10,000 pairs of mixed samples whit control and ADHD subjects). Results: the present method reduced the range of p'-values that did not show covariance with neighbors (type I and also type-II errors). The differences between simulation or raw p-vector and corrected p-vectors were, respectively, minimal and maximal for window length set by autocorrelation in p-vector convolution. Comparison with existing methods: Our method was less conservative while FDR methods rejected basically all significant p-values for Pz and O2 channels. The MC simulations, gold-standard method for error correction, presented 2.78±4.83% of difference (all 20 channels) from p-vector after correction, while difference between raw and corrected p-vector was 5,96±5.00% (p = 0.0003). Conclusion: As a cluster-based correction, the present new method seems to be biological and statistically suitable to correct p-values in mass univariate analysis of ERP waves, which adopts adaptive parameters to set correction.

The data is a simulation of confidence limits, coverage probabilities, average difference from actual values, and expected interval width for misclassified binomial proportions. The methods used for estimation include a modified Zao and Li (ZL), and adjusted Wilson (WL) interval. individual sheets are for different sample sizes.

Shape files (see also Scotland study area.shp) for the mapping the intermediate zones for Scotland.

This dataset is about book subjects and is filtered where the books includes Applied statistics : analysis of variance and regression, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

Advances and Applications in Mathematical Sciences Acceptance Rate - ResearchHelpDesk - The Advances and Applications in Mathematical Sciences (ISSN 0974-6803) is a monthly journal. The AAMS's coverage extends across the whole of mathematical sciences and their applications in various disciplines, encompassing Pure and Applied Mathematics, Theoretical and Applied Statistics, Computer Science and Applications as well as new emerging applied areas. It publishes original research papers, review and survey articles in all areas of mathematical sciences and their applications within and outside the boundary.

Acoustic data used for the supervised and unsupervised seabed classification using Functional Data Analysis and Time Series clustering from acoustic curves

Simulated datasets used in the supplement with large group size of 30, log-scale noise levels and zero proportions.The settings are reflected in the title of the data:(1) large: group size = 30; (2) 0.5, 1, 1.5: the log-scale noise level(3) 0.3, 0.4, 0.5: the extra zero proportion(4) The last number is the index of replicates. There are 50 replicates for each setting

Explore the progression of average salaries for graduates in Mathematics, Applied Statistics And Informatics from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Mathematics, Applied Statistics And Informatics relative to other fields. This data is essential for students assessing the return on investment of their education in Mathematics, Applied Statistics And Informatics, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Applied Statistics, Social Sciences And Humanities from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Applied Statistics, Social Sciences And Humanities relative to other fields. This data is essential for students assessing the return on investment of their education in Applied Statistics, Social Sciences And Humanities, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Computer Science, Applied Statistics, And Actuarial Science from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Computer Science, Applied Statistics, And Actuarial Science relative to other fields. This data is essential for students assessing the return on investment of their education in Computer Science, Applied Statistics, And Actuarial Science, providing a clear picture of financial prospects post-graduation.

Code Examples from the Book

Talk given at International Biometrics Conference, Victoria, July 2016Session: Modelling Count Data in the Era of Next Generation Sequencing Datahttp://f1000research.com/articles/5-1356/v1http://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0862-3http://f1000research.com/articles/4-1521/v2

Here is the programme used to produce the analyses and graphs for the "Cross-sectional and longitudinal associations of obesity with disability between age 50 and 90 in the SHARE study" paper. This programme includes STATA v17 codes.

A centered parameterization of the eight schools model. Provided as an example of a model that NUTS has trouble fitting. The eight schools model is a hierarchical model used for an analysis of the effectiveness of classes that were designed to improve students' performance on the Scholastic Aptitude Test. See Bayesian Data Analysis (Gelman et. al.) for more details.

Supplementary MaterialData filesFigures A1 - A8: Simulations BoxplotsFigures B1: B16: Application Dendrograms Software: R and Matlab

Explore the progression of average salaries for graduates in Applied Statistics Analytics from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Applied Statistics Analytics relative to other fields. This data is essential for students assessing the return on investment of their education in Applied Statistics Analytics, providing a clear picture of financial prospects post-graduation.

This table of language of work profile information was extracted from the Statistics Canada website. It contains the information gathered during the 2021Census with respect to the population within a Dissemination Area and the breakdown of this population by language most commonly spoken at work. This data covers the Dissemination Area in York Region only.Statistics Canada has suppressed the profiles for certain areas due to very low population count. Suppressed areas will appear as NULL values in the attribute table.For more information on 2021Census information: https://www12.statcan.gc.ca/census-recensement/2021/dp-pd/prof/details/download-telecharger.cfm?Lang=E&SearchText=York&DGUIDlist=2021A00033519&GENDERlist=1,2,3&STATISTIClist=1&HEADERlist=0Please exercise caution if using dissemination areas to roll up (aggregate) to other levels of census geographies, due to greater suppression applied by Statistics Canada at dissemination area. Interested in viewing and interacting with this data even more? Visit the York Region Census Explorer Dashboard to gain high level insights from this data at the municipal and regional level for York Region.

The increase or decrease in the speed and accuracy of tasks is a measure of mental work performance in the aspect of mental fatigue