level of significance

USAGE SUMMARY

'level of significance' is correct and usable in written English.
It is a phrase used to describe the degree to which an effect or result is meaningful or important. For example: The level of significance seen in the results of this experiment suggest that there is a strong correlation between the two variables.

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

aStatistically significant at 0.05 level of significance.

International Journal of Energy and Environmental Engineering

*Statistically significant at 5% level of significance.

BMC Medical Informatics and Decision Making

Both findings are significant at the 5% level of significance.

IZA Journal of Labor Economics

level of significance.

Heritage Science

Level of significance was established at 5%.

The Journal of Headache and Pain

The level of significance was 0.05.

The Journal of Headache and Pain

The level of significance is 0.001.

EURASIP Journal on Wireless Communications and Networking

The level of significance was P < 0.05.

The Journal of Headache and Pain

The level of significance was α=5%.

The Journal of Prosthetic Dentistry

Level of significance was set at 5%.

Theriogenology

χ2 test with 5% level of significance was used.

The Journal of Headache and Pain

Expert writing Tips

Best practice

When reporting statistical results, clearly state the "level of significance" used (e.g., p < 0.05) to allow readers to properly interpret your findings.

Common error

Do not assume that statistical significance automatically implies practical importance. A statistically significant result at a certain "level of significance" may still have a small effect size or limited real-world relevance.

Linguistic Context

The phrase "level of significance" functions as a technical term within statistical analysis. It indicates the threshold for determining whether a result is statistically significant, as confirmed by Ludwig AI.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

The phrase "level of significance" is a fundamental concept in statistics, denoting the threshold for determining statistical significance. Ludwig AI confirms its correctness and common usage, particularly within scientific and academic contexts. It's crucial to understand that while a result might be statistically significant, as indicated by the chosen "level of significance", it does not automatically imply practical importance. Common related terms include "statistical significance level" and "alpha level". When writing, always clearly state the "level of significance" used to facilitate proper interpretation of results.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

statistical significance level

This alternative is more specific, explicitly stating the statistical context.

alpha level

This alternative uses the statistical symbol α, commonly used to denote the level of significance.

significance threshold

This alternative focuses on the boundary or cutoff point for determining significance.

critical value

This alternative refers to the value against which a test statistic is compared to determine significance.

p-value threshold

This alternative refers to the probability value used to assess statistical significance.

statistical threshold

This alternative emphasizes the statistical boundary for interpreting results.

confidence level

This alternative focuses on the degree of certainty associated with a statistical result.

margin of error

This alternative describes the degree of uncertainty in a statistical estimate.

acceptable risk of error

This alternative describes the tolerance for making an incorrect conclusion.

degree of certainty

This alternative broadens the concept to any degree of assurance in a result.

FAQs

How is the "level of significance" determined in research?

The "level of significance" is typically set before conducting research, often at 0.05 (5%), indicating the probability of rejecting a true null hypothesis. This choice reflects a balance between the risk of false positives and false negatives.

What does a p-value less than the "level of significance" mean?

A p-value less than the predetermined "level of significance" (e.g., 0.05) suggests that the results are statistically significant. This indicates strong evidence against the null hypothesis, leading to its rejection.

How does the sample size affect the "level of significance"?

Larger sample sizes can increase the statistical power, making it easier to detect significant results even with small effect sizes. Therefore, with larger samples, even minor deviations can reach the chosen "level of significance".

What are some alternatives to using a 0.05 "level of significance"?

Depending on the field and the research question, you might use a more stringent "alpha level" such as 0.01 to reduce the risk of false positives, or consider using methods like Bayesian analysis which offer different frameworks for assessing evidence.