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Statistical Test Selector
Map outcome type, groups, pairing, and research objective to candidate statistical tests with assumptions and related calculators.
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Browser-local research workflow utilities for test selection, Likert analysis, review matrices, SLR searches, PRISMA counts, APA wording, data-cleaning checks, thesis planning, codebooks, and journal readiness.
Research tools support academic workflow planning without AI APIs or server-side storage. Use them to select candidate statistical tests, summarize Likert responses, build literature-review matrices, draft systematic-review search strings, organize PRISMA screening counts, format statistical result wording, document data-cleaning readiness, plan thesis chapters, build questionnaire codebooks, and check journal submission readiness.
10 tools
Published helper entries in this category.
Map outcome type, groups, pairing, and research objective to candidate statistical tests with assumptions and related calculators.
Analyze numeric Likert responses with category counts, agreement share, central tendency, visual output, and export files.
Organize citations, designs, methods, findings, themes, and research gaps into an exportable matrix.
Combine research concepts and synonyms into Boolean search strings with PubMed-oriented variants and documentation notes.
Enter review screening counts and generate a checked flow table, visual, and exportable summary.
Convert supplied test statistics into readable APA-style result sentences with assumptions and non-proof wording.
Review missing values, coding, duplicates, outliers, variable labels, audit trail, and reproducibility readiness.
Turn chapter notes into a sequenced writing plan with objectives, evidence needs, outputs, and review checkpoints.
Document survey variables, labels, coding, missing values, reverse scoring, and analysis notes.
Review scope, reporting guideline, ethics, author contributions, figures, references, data availability, and submission files.
They support students, reviewers, and researchers organizing evidence, study planning, reporting, screening counts, codebooks, and manuscript preparation without replacing supervision or methodological review.
It uses the research goal, outcome type, number of groups, independence or pairing, and key assumptions to suggest methods for further review.
Useful columns include citation, purpose, design, sample, measures, analysis, findings, limitations, quality notes, and relevance to the review question.
Pilot it in each target database, check known relevant studies, adapt controlled vocabulary and field syntax, and record every version and search date.
Identification, deduplication, screening, exclusion, eligibility, and inclusion totals should form an auditable path without unexplained gains or losses.
Include the analysis, statistic, degrees of freedom where applicable, p-value, effect size, confidence interval, and cautious interpretation that matches the actual output.
No. It documents variable names, labels, response codes, missing rules, units, and derivations, while the source instrument remains the authority for wording and routing.
No. It checks submission preparation and reporting completeness but cannot predict editor fit, peer review, novelty assessment, or publication decisions.
Research Tools structure study-design decisions, questionnaire summaries, literature extraction, search drafts, screening counts, codebooks, cleaning checks, writing plans, and submission checks.
Begin with the approved protocol or institutional requirement, enter traceable source-based notes, generate the structured artifact, resolve warnings, and verify the export against articles, instruments, ethics records, or journal instructions.
These utilities organize user-entered information and do not approve methods, assess evidence quality automatically, replace supervision, or guarantee journal acceptance. Source records remain authoritative.