statistical significance level

USAGE SUMMARY

"statistical significance level" is a correct phrase that can be used in written English.
It is most typically used when discussing the results of statistical tests, such as a t-test or chi-square test, to describe the likelihood that a certain outcome occurred. Example: The data from the t-test showed that there was a statistically significant difference between the control group and the treatment group, with a significance level of 0.05.

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

A statistical significance level of 0.05 was considered significant.

Critical Care

There was, however, a reduction in the cumulative incidence of relapse in the ASCT arm, which reached the statistical significance level.

Nature

Statistical significance level of P < 0.05.

Intensive Care Medicine Experimental

The statistical significance level was p < 0.05.

Maxillofacial Plastic and Reconstructive Surgery

The statistical significance level was set to 0.05.

Nanoscale Research Letters

A two-sided statistical significance level of <0.05 was adopted.

Intensive Care Medicine Experimental

The statistical significance level was 5% (p < 0.05).

International Journal of Implant Dentistry

The statistical significance level was set at P < 0.005.

Genus

The statistical significance level was set at p < 0.05.

The Journal of Headache and Pain

Statistical significance level was set at p < 0.05.

Intensive Care Medicine Experimental

The statistical significance level was set to P ≤ 0.05.

Ecological Processes

Expert writing Tips

Best practice

Clearly state the "statistical significance level" (e.g., p < 0.05) early in your research report to define the threshold for determining statistically significant results.

Common error

Avoid assuming that a statistically significant result is automatically clinically meaningful. Always consider the effect size and practical implications alongside the "statistical significance level".

Linguistic Context

The phrase "statistical significance level" functions as a noun phrase that quantifies the threshold for determining the statistical significance of results. As Ludwig AI confirms, this phrase is suitable for use in written English. Its usage is typically related to academic, scientific or research-oriented writing and as Ludwig shows, is common in scientific publications.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

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Ludwig's WRAP-UP

The phrase "statistical significance level" is a commonly used noun phrase in scientific and academic writing. As Ludwig AI confirms, it's a correct and well-understood term. It defines the threshold (often p < 0.05) for determining whether a result is statistically significant. While grammatically sound and widely accepted, it's crucial to avoid confusing statistical significance with clinical importance. Alternative phrases include "alpha level" and "significance threshold". Remember to clearly state your chosen level and consider the implications of Type I and Type II errors in your research.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

level of significance

A slightly reworded version of the original phrase, maintaining the core meaning.

predetermined significance level

Emphasizes that the significance level is decided prior to analysis.

significance threshold

Emphasizes the boundary beyond which results are considered significant.

p-value threshold

Specifically highlights the p-value as the criterion for significance.

critical p-value

Highlights the specific p-value used as the cutoff for determining significance.

alpha level

Refers specifically to the probability of rejecting the null hypothesis when it is true.

alpha value

Shorthand term directly referencing the probability of type I error.

statistical cut-off

General term for the point at which statistical results are deemed meaningful.

rejection region

Statistical term that describes the values for which the null hypothesis is rejected.

confidence level

Related concept focusing on the degree of certainty in a statistical result, not directly the significance threshold.

FAQs

How is "statistical significance level" commonly expressed in research papers?

Typically, the "statistical significance level" is represented by α (alpha) or p-value, often set at 0.05, meaning there's a 5% risk of concluding there's an effect when none exists. For instance, you might see statements like "p < 0.05" or "α = 0.05".

What does it mean if a result is not statistically significant at the chosen "statistical significance level"?

If a result isn't statistically significant, it doesn't automatically mean there's no effect. It simply means that the observed data doesn't provide strong enough evidence to reject the null hypothesis at the predetermined "statistical significance level". A larger sample size or a different experimental design might reveal a significant effect.

What's the difference between setting a "statistical significance level" of 0.05 versus 0.01?

A "statistical significance level" of 0.01 ("p less than 0.01") is more stringent than 0.05 ("p less than 0.05"). Choosing 0.01 reduces the chance of a false positive (Type I error) but increases the risk of a false negative (Type II error). The choice depends on the specific research question and the consequences of each type of error.

Are there alternatives to using a fixed "statistical significance level"?

Yes, some researchers advocate for methods like Bayesian statistics, which provide probabilities of hypotheses being true rather than relying on a fixed "statistical significance level". Others suggest focusing on effect sizes and confidence intervals to provide a more nuanced interpretation of results.