Statistical test

USAGE SUMMARY

The phrase "Statistical test" is correct and usable in written English.
It can be used 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

Statistical test: ANOVA.

Annals of Intensive Care

Statistical test: Chi square test.

Intensive Care Medicine Experimental

Statistical test (Student's test) was performed.

Annals of Intensive Care

Statistical test indicated.

eLife

Statistical test: Student's t test.

Critical Care

Statistical test used was two-way ANOVA.

Arthritis Research and Therapy

Statistical test Chi-square was done.

BMC Infectious Diseases

Statistical test used was Chi-square.

BMC Pulmonary Medicine

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

Expert writing Tips

Best practice

When reporting the results of a "statistical test", always specify the specific test used (e.g. t-test, ANOVA, chi-square) and the resulting p-value to provide transparency and allow for reproducibility.

Common error

Avoid assuming that a statistically significant result is necessarily practically important. Consider the effect size and the context of your research to determine the real-world implications of the "statistical test" results.

Linguistic Context

The phrase "statistical test" functions as a noun phrase, often serving as the subject or object of a sentence. It describes a method or procedure used to analyze data and draw conclusions. Ludwig AI provides numerous examples of its usage in scientific research and statistical reporting.

Expression frequency: Very common

Frequent in

Science

65%

News & Media

18%

Formal & Business

10%

Less common in

Encyclopedias

3%

Wiki

2%

Reference

2%

Ludwig's WRAP-UP

The phrase "statistical test" is a common and correct term used to describe methods for analyzing data and drawing conclusions. Ludwig AI’s analysis indicates its primary function is to describe specific analytical methods in research and statistical reporting. Predominantly found in formal and scientific contexts, its use helps ensure clarity and transparency in communicating research findings. When using "statistical test", specifying the exact test and p-value is crucial. While statistically significant results are valuable, interpreting practical significance within the study's context is essential. This comprehensive guide helps ensure accurate and effective usage.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Hypothesis test

Focuses on the process of testing a specific hypothesis using statistical methods.

Significance test

Highlights the assessment of statistical significance in the results.

Data analysis technique

Emphasizes the broader methodology used to analyze data.

Inferential statistics

Refers to the branch of statistics concerned with drawing inferences from a sample to a population.

Statistical procedure

Highlights the specific steps and methods used in the statistical analysis.

Test of significance

Similar to significance test, but emphasizes the act of testing.

Quantitative analysis

Broader term referring to any analysis that involves numerical data.

Statistical method

Focuses on the specific approach or method used in statistical analysis.

Mathematical model

Highlights the mathematical representation used in the analysis.

Statistical evaluation

Emphasizes the process of evaluating data using statistical principles.

FAQs

How do I properly report the results of a "statistical test"?

When reporting the results, include the name of the test, the test statistic, degrees of freedom (if applicable), and the p-value. For example: "A t-test revealed a significant difference (t(20) = 2.5, p < 0.05)".

What's the difference between a one-tailed and two-tailed "hypothesis test"?

A one-tailed test is used when you predict the direction of an effect, while a two-tailed test is used when you only predict that an effect exists. The choice depends on your hypothesis and can affect the p-value.

What are some common examples of "data analysis techniques" that qualify as "statistical tests"?

Common examples include t-tests, ANOVA, chi-square tests, regression analysis, and correlation analysis, each suited for different types of data and research questions.

How do I choose the appropriate "statistical test" for my data?

Consider the type of data (categorical or continuous), the number of groups being compared, and whether the data meets the assumptions of the test (e.g., normality, independence). Consulting with a statistician is often helpful.