statistical test

USAGE SUMMARY

The phrase "statistical test" is correct and usable in written English.
You can use it when referring to a method or procedure used to analyze data and draw conclusions based on statistical principles. Example: "To determine the significance of the results, we conducted a statistical test to analyze the data collected from the experiment."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Kolmogorov-Smirnov is a statistical test.

The New Yorker

The analysts then ran a statistical test to measure clustering between regions of similar word preference.

The Guardian

The results were analysed using a statistical test.

The Economist

A new study builds on this research by applying a sensitive statistical test borrowed from outside the investment world.

The New York Times

Statistical test: ANOVA.

Annals of Intensive Care

Pew Research Center challenges statistical test.

Science Magazine

But this is not a statistical test.

SEP

Statistical test: Chi square test.

Intensive Care Medicine Experimental

No statistical test of heterogeneity was performed.

Journal of Patient-Reported Outcomes

Statistical test (Student's test) was performed.

Annals of Intensive Care

A statistical test depends greatly on sampling.

Journal of Inequalities and Applications

Expert writing Tips

Best practice

Clearly state the "statistical test" used when reporting research results to ensure transparency and reproducibility. For instance, specify whether you conducted a t-test, ANOVA, or chi-squared test.

Common error

Avoid equating a statistically significant p-value (e.g., p < 0.05) with practical significance or real-world importance. Statistical significance only indicates that the observed result is unlikely to have occurred by chance, not that it is necessarily meaningful or impactful.

Linguistic Context

The phrase "statistical test" functions as a noun phrase, typically used as the subject or object in a sentence. It denotes a specific method or procedure employed to analyze data and draw conclusions based on statistical principles. Ludwig AI confirms its common usage.

Expression frequency: Very common

Frequent in

Science

61%

News & Media

20%

Formal & Business

19%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "statistical test" is a common and grammatically correct term referring to methods used to analyze data and draw conclusions. As confirmed by Ludwig AI, its frequent use spans across scientific research, news reporting, and business analysis. When writing, clearly specify the "statistical test" used, and be cautious about misinterpreting p-values. Common types include t-tests, ANOVA, and chi-squared tests. Choosing the right "statistical test" is crucial for valid results.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

test of significance

Reorders the words while retaining the original meaning, placing emphasis on assessing the importance of results.

significance test

Emphasizes the determination of statistical significance, highlighting the outcome of whether results are likely due to chance.

hypothesis test

Focuses on the testing of a specific hypothesis using statistical methods, implying a more targeted approach than a general statistical test.

statistical procedure

More formal way to describe the specific steps involved in a statistical test.

statistical analysis technique

Highlights the technical nature of the test, framing it as a specific method within statistical analysis.

data analysis method

Broader term encompassing various techniques for examining data, including but not limited to statistical tests.

method of statistical inference

Focuses on drawing conclusions from data using statistical methods, presenting a more theoretical perspective.

quantitative analysis

Describes the overall process of using numerical data for analysis, which may involve statistical tests.

evaluation of statistical significance

Highlights the interpretative aspect of results of statistical tests.

empirical verification

Emphasizes the use of evidence and observation to confirm or reject a hypothesis, suggesting a practical application of a statistical test.

FAQs

What are some common types of statistical tests?

Common types of statistical tests include t-tests, ANOVA, chi-squared tests, regression analysis, and correlation analysis. The choice of test depends on the type of data and the research question being addressed.

How do I choose the right statistical test?

Selecting the appropriate "statistical test" depends on several factors, including the type of data (continuous, categorical), the number of groups being compared, and the research question. Consulting with a statistician can be helpful in making this determination.

What does it mean for a statistical test to be "significant"?

A significant "statistical test" result (typically indicated by a p-value below a pre-defined threshold, such as 0.05) suggests that the observed effect is unlikely to be due to random chance. It doesn't necessarily imply practical importance or causation.

What is the difference between a parametric and a non-parametric statistical test?

Parametric tests assume that the data follows a specific distribution (e.g., normal distribution), while non-parametric tests do not make such assumptions. Non-parametric tests are often used when data is not normally distributed or when dealing with ordinal or nominal data.