On reading Youden: Learning about the practice of statistics and applied statistical research from a master applied statistician |
510:Y |
QCAS / 69 / 1-2 / 71 |
Evaluating Wikipedia as a self-learning resource for statistics: You know they’ll use it |
510:T |
QCAS / 66 / 5-6 / 389 |
Construction of row-column factorial designs |
510:Y |
QCAS / 66 / 1-2 / 59 |
Introduction to double robust methods for incomplete data |
510:Y |
QCAS / 65 / 3-4 / 243 |
Detecting deviating data cells |
510:Y |
QCAS / 65 / 3-4 / 245 |
Analyzing behavioral big data – Methodological, practical, ethical and moral issues |
510:Y |
QCAS / 63 / 5-6 / 437 |
Statistical and computational challenges in whole genome
prediction and genome-wide association analyses
for plant and animal breeding |
510:B |
QCAS / 62 / 1-2 / 77 |
The conditional in-control performance
of self-starting control charts |
510:Y |
QCAS / 62 / 1-2 / 79 |
Computer experiments with qualitative and quantitative variables: A review and reexamination |
510:Y |
QCAS / 61 / 1-2 / 73 |
Multiplicative methods for computing D-optimal stratified designs of experiments |
510:Y |
QCAS / 60 / 1-2 / 67 |
Ratings and rankings: Voodoo or science? |
510:Y |
QCAS / 60 / 1-2 / 69 |
So many variables, so few observations |
510:Y |
QCAS / 59 / 5-6 / 465 |
Follow the fundamentals: Four data analysis basics will help you do big data projects the right way |
510:Y |
QCAS / 59 / 5-6 / 469 |
The effect of aggregating data when monitoring a Poisson process |
510:Y |
QCAS / 59 / 3 / 223 |
Heart of the matter: Understanding variation and its relationship to quality |
510:Y |
QCAS / 59 / 1-2 / 95 |
Animation: An R package for creating animations and demonstrating statistical methods |
510:Y |
QCAS / 59 / 1-2 / 97 |
Systems with multiple data sources: A case study on making statistical tools accessible to engineers |
510:Y |
QCAS / 58 / 4 / 347 |
Statistical engineering perspective on planetary entry,
descent, and landing research |
510:Y |
QCAS / 58 / 3 / 223 |
Aerospace research through statistical engineering |
510:Y |
QCAS / 58 / 3 / 225 |
A partially linear regression model for data from an outcome-dependent sampling design |
510:Y |
QCAS / 58 / 1-2 / 75 |
Missing data in a stochastic Dollo model for binary trait data, and its application to the dating of Proto-Indo-European |
510:Z |
QCAS / 57 / 3 / 233 |
Mixed signals: Prevent confusion about statistical terms that have multiple meanings |
510:Y |
QCAS / 56 / 5-6 / 491 |
Karl Pearson’s meta analysis revisited |
510:Y |
QCAS / 55 / 5-6 / 493 |
Assessment of a binary measurement system in current use |
510:Y |
QCAS / 55 / 5-6 / 495 |
Monitoring the slopes of linear profiles |
510:Y |
QCAS / 55 / 1-2 / 73 |
Calculated decisions: An alternative to data transformation is to find a non-normal distribution |
510:Y |
QCAS / 54 / 3 / 235 |
On estimation of variance in successive sampling |
510:Y |
QCAS / 54 / 1-2 / 75 |
The reality of residual analysis |
510:Y |
QCAS / 54 / 1-2 / 77 |
Data conformance testing by digital analysis – A critical review and an approach to more appropriate testing |
510:Y |
QCAS / 53 / 6 / 585 |
Exploratory data analysis in quality-improvement projects |
510:Y |
QCAS / 53 / 4-5 / 445 |
Modelling price paths in on-line auctions: smoothing sparse and unevenly sampled curves by using semiparametric mixed models |
510:Z |
QCAS / 53 / 4-5 / 447 |
Darwinian evolution in parallel universes: A parallel genetic algorithm for variable selection |
510:Y |
QCAS / 52 / 5 / 529 |
Detecting answer copying when the regular response process follows a known response model |
510:Y |
QCAS / 52 / 5 / 533 |
On the accuracy of statistical procedures in Microsoft Excel 2003 |
510:Y |
QCAS / 52 / 2 / 191 |
Principal directions of the general Pareto distribution with applications |
510:Y |
QCAS / 52 / 1 / 73 |
How to lie with bad data |
510:Y |
QCAS / 51 / 3 / 287 |
The most-cited statistical papers |
510:Y |
QCAS / 51 / 2 / 211 |
John W. Tukey and data analysis |
510:Y |
QCAS / 49 / 5 / 549 |
John Tukey and robustness |
510:Y |
QCAS / 49 / 5 / 553 |
Statistical fraud detection: A review |
510:Y |
QCAS / 49 / 3 / 313 |
Testing non-nested multivariate effect size models in meta-analysis |
510:Y |
QCAS / 48 / 6 / 655 |
Deming and the proactive statistician |
510:Y |
QCAS / 48 / 4 / 421 |
Statistical modeling: The two cultures |
510:Y |
QCAS / 48 / 1 / 81 |
Three approaches to analyze quality data originating in nonnormal populations |
510:Y |
QCAS / 47 / 1 / 77 |
Three approaches to analyze quality data originating in non-normal populations |
510:Y |
QCAS / 46 / 5 / 547 |
Should the median test be retired from general use? |
510:Y |
QCAS / 46 / 4 / 433 |
Data mining for fun and profit |
510:Y |
QCAS / 46 / 3 / 311 |
Large data series: Modeling the usual to identify the unusual |
510:Y |
QCAS / 46 / 2 / 189 |
Managing data quality in a statistical agency |
510:Y |
QCAS / 45 / 6 / 665 |
A comparison of multiresponse optimization: Sensitivity to parameter selection |
510:Y |
QCAS / 45 / 5 / 545 |
An application of multivariate analysis in product development in the food industry |
510:Y |
QCAS / 45 / 5 / 549 |
From association to causation: Some remarks on the history of statistics |
510:Y |
QCAS / 45 / 4 / 439 |
Effective data collection |
510:Y |
QCAS / 45 / 3 / 317 |
On the accuracy of statistical procedures in Microsoft Excel 97 |
510:Y |
QCAS / 45 / 3 / 319 |
Measurement: Methods comparisons and linear statistical relationship |
510:Y |
QCAS / 45 / 2 / 197 |
Some statistical heresies |
510:Y |
QCAS / 45 / 1 / 85 |