Whom does INTVL help?
Doctors and health professionals
INTVL is ideal for the medical field, covering some of the most widely used statistics and definitions in medicine and health research.
Academics
INTVL helps you deal with reporting bias in the academic literature by generating insightful statistics that are often not reported, in a flash.
Use it to review other studies or for your own projects (some of our calculators and converters are not readily available in many renowned computer software).
Scientists and researchers
Its calculators are powerful and accurate enough to perform various scientific calculations and probably most research applications you can think of.
Students and junior researchers
Its friendly and informative UI makes it great to get a better understanding of core statistical and mathematical concepts and learn how to correctly interpret some of the most widely used statistics in applied research.
What do you get with the paid version?
Eleven statistical calculators and converters, with more on the way!
- Confidence interval (CI) calculators for major statistics used in primary studies and meta-analyses.
- Prediction interval (PI) generators for meta-analyses results.
- P value to confidence interval converters.
Top-of-the-line glossary based on authoritative sources, including over 200 interlinked definitions in various fields, including medicine, statistics, and mathematics.
Free updates with new calculators, converters, definitions, and features.
No in-app ads, not now, not ever.
No data collection
Key features
- Easy to use
- Fast
- Accurate
- Informative
An edge in research
CIs for proportions
Unlike crude proportions, CIs offer information about the precision of the estimate and the population from which the sample was drawn.
CIs for means
Similar to proportions, crude means do not say anything about precision or the population and mental calculations of a CI using a standard deviation or standard error (if reported) may be inconvenient and will not be as precise as when using a calculator.
P values to CIs
Unlike a p value, a CI can be more than a simple indicator of statistical significance and give you clues about the precision of an estimate and family of alternatives in the short term or about the size and direction of the effect in the long run.
PIs to assess heterogeneity in meta-analyses
- The CI of a pooled effect estimate is like an average of averages and does not tell us how the true effect size varies across populations and, therefore, how much heterogeneity exists in a meta-analysis.
- The p value for the Chi squared test only tells us if there is or is no significant heterogeneity;
- The I squared statistic only tells us what percentage (%) of the variance we observe is due to heterogeneity;
- The Tau and Tau squared statistics give us an indication in regard to the amount of heterogeneity present but may be very inconvenient to use in mental calculations.
Compared to the above statistics, PIs can reveal the amount of heterogeneity more directly and, at the same time, tell us how significantly it impacts the estimation.
Probably the best glossary in the world for statistical intervals
We have reviewed some of the worlds most authoritative sources to build a highly consistent vocabulary that includes well-defined inter-linked definitions.