C1 Expression Formel 3 min de lecture

The effect size was

Research methodology and reporting expression

Use this phrase to explain the real-world impact and strength of your data-driven findings.

En 15 secondes

  • Describes the strength of a relationship between variables.
  • Used in research, data analysis, and professional reporting.
  • Indicates if a result has practical, real-world importance.

Signification

This phrase is used to describe how strong or meaningful a result is in a study or experiment. It tells you if a change was a tiny ripple or a massive wave in the real world.

Exemples clés

3 sur 6
1

Presenting a marketing report

The effect size was substantial, showing that the new ads really drove sales.

The impact was large, proving the new ads worked well.

💼
2

Writing a university thesis

Although the results were significant, the effect size was relatively small.

The results were real, but the actual impact was tiny.

👔
3

Discussing a new diet with a friend (humorous)

I stopped eating sugar for a week, but the effect size was basically zero.

I quit sugar but didn't see any real change.

😄
🌍

Contexte culturel

The phrase became a cornerstone of modern research after the American Psychological Association (APA) began emphasizing its importance over simple 'significance' in the late 1990s. It reflects a Western cultural shift toward data-driven decision-making and evidence-based practice. In global business, it is the preferred way to discuss ROI (Return on Investment) in a more scientific manner.

💡

Pair with Adjectives

Always have an adjective ready like 'small', 'medium', 'large', or 'negligible' to follow the phrase.

⚠️

Don't confuse with P-Value

A p-value tells you IF something happened; the effect size tells you HOW MUCH it happened. Don't mix them up!

En 15 secondes

  • Describes the strength of a relationship between variables.
  • Used in research, data analysis, and professional reporting.
  • Indicates if a result has practical, real-world importance.

What It Means

Imagine you try a new coffee brand to stay awake. You feel a little more alert. The effect size was is the way researchers describe exactly *how much* more alert you felt. It doesn't just say "it worked." It measures the "oomph" or the strength of the result. In the world of data, it helps us understand if a discovery actually matters. A result can be "statistically significant" but have a tiny effect size. That means the result is real, but it’s too small to care about. This phrase focuses on the practical impact of your findings.

How To Use It

You usually follow this phrase with a descriptor or a number. You might say The effect size was large or The effect size was 0.5. It almost always appears when you are summarizing data. You can use it to compare two different things, like two teaching methods. It helps your audience visualize the magnitude of your discovery. Think of it as the difference between saying "it's hot" and "it's 100 degrees." It adds precision to your claims. You’ll sound like a data-savvy pro when you use it correctly.

When To Use It

Use this in any professional or academic setting involving data. It’s perfect for university essays, lab reports, or business presentations. If you are a marketer showing how a campaign worked, use it. If you are a doctor discussing a new treatment, use it. It’s the gold standard for reporting results in the 21st century. It shows you aren't just looking at surface-level numbers. You are looking at the actual weight of the evidence. It’s a very impressive phrase in a boardroom or a classroom.

When NOT To Use It

Avoid this phrase in casual, everyday conversations with friends. If you say The effect size was small regarding a movie you watched, you’ll sound like a robot. It’s too clinical for emotional or social situations. Don't use it when you are guessing or being vague. It implies you have actually measured something. Using it without data makes you look like you’re trying too hard to sound smart. Keep it away from your dating life or your pizza orders. It’s a tool for analysis, not for small talk.

Cultural Background

This phrase rose to fame because of the "replication crisis" in science. For years, researchers only cared about "p-values," which just say if a result is a fluke. But people realized that tiny, useless results were being called "significant." The scientific community shifted toward effect size to ensure honesty. It represents a cultural move toward transparency and practical value in research. It’s now a mandatory part of reporting in psychology, medicine, and social sciences. It’s the "show me the money" of the academic world.

Common Variations

You might hear people say The magnitude of the effect. In specific circles, they might say The Cohen’s d was... which is a type of effect size. Some might simply say The impact was substantial. However, The effect size was remains the most formal and standard way to start the sentence. It signals to your reader that a serious statistical explanation is coming next. It’s a classic "researcher" sentence starter.

Notes d'usage

This is a high-level C1/C2 expression. It is almost exclusively used in formal writing, research, and data-heavy business environments. Using it correctly signals a high level of education and analytical skill.

💡

Pair with Adjectives

Always have an adjective ready like 'small', 'medium', 'large', or 'negligible' to follow the phrase.

⚠️

Don't confuse with P-Value

A p-value tells you IF something happened; the effect size tells you HOW MUCH it happened. Don't mix them up!

💬

The 'So What?' Factor

In English-speaking academic culture, using this phrase answers the 'So what?' question that professors always ask.

Exemples

6
#1 Presenting a marketing report
💼

The effect size was substantial, showing that the new ads really drove sales.

The impact was large, proving the new ads worked well.

Used here to justify a budget spend on advertising.

#2 Writing a university thesis
👔

Although the results were significant, the effect size was relatively small.

The results were real, but the actual impact was tiny.

A common academic nuance used to show critical thinking.

#3 Discussing a new diet with a friend (humorous)
😄

I stopped eating sugar for a week, but the effect size was basically zero.

I quit sugar but didn't see any real change.

Using formal language for a mundane personal experience for comedic effect.

#4 Texting a colleague about a software update
😊

We ran the speed test; the effect size was huge after the patch.

The update made a massive difference in speed.

Casual professional shorthand for 'the change was very noticeable'.

#5 A doctor explaining a study to a patient
💼

In the clinical trial, the effect size was moderate for this medication.

The medicine worked reasonably well for most people.

Used to set realistic expectations for a treatment.

#6 Reflecting on a life change
💭

I moved to the countryside, and the effect size on my stress was massive.

Moving to the country helped my stress levels a lot.

Applying a technical term to a personal emotional state.

Teste-toi

Choose the best adjective to complete the sentence in a research context.

The study was successful, and the effect size was ___, suggesting a major breakthrough.

✓ Correct ! ✗ Pas tout à fait. Rponse correcte : large

In research, 'large' is the standard adjective used to describe a strong effect size.

Complete the professional report sentence.

The ___ size was calculated to determine the practical significance of the trial.

✓ Correct ! ✗ Pas tout à fait. Rponse correcte : effect

The standard term is 'effect size' when discussing the magnitude of a result.

🎉 Score : /2

Aides visuelles

Formality of 'The effect size was'

Casual

Talking to friends about a movie.

It was a big deal.

Neutral

Explaining a project to a coworker.

The impact was pretty clear.

Formal

Writing a scientific paper or business report.

The effect size was statistically significant.

Where to use 'The effect size was'

The effect size was
📖

Academic Journal

Reporting findings of a psychological study.

👔

Corporate Boardroom

Analyzing the success of a new product launch.

💊

Medical Review

Evaluating the efficacy of a new drug.

💻

Tech Startup

Reviewing user engagement data after a UI change.

Questions fréquentes

10 questions

It is a quantitative measure of the magnitude of a phenomenon. It tells you how strong the relationship between two groups is in a way that is easy to understand.

Only if you are talking about work or data. In a truly casual email to a friend about your weekend, it would sound very strange and overly formal.

While it comes from statistics, it is used in any field that relies on evidence, including social work, education, and marketing. It’s about evidence, not just numbers.

It depends on the field! In some sciences, 0.2 is small, 0.5 is medium, and 0.8 is large. Always check the context of what you are studying.

It is used globally in English-speaking academia and business. There is no major difference in how it is used between the US, UK, or Australia.

Yes, it can. A negative effect size usually means the intervention had the opposite effect of what was expected, like a medicine making people feel worse.

Saying the effect size was large is much more precise and professional. It suggests you have used a specific formula to reach that conclusion.

Not always. You can use a descriptive word like substantial or minimal if you are just summarizing the main point for a general audience.

They are similar, but effect size is the technical term. Use impact in a speech and effect size in a written report for the best results.

The most common mistake is using it to describe something that wasn't measured. Don't say the effect size was huge about your lunch unless you actually did a study on it!

Expressions liées

Statistically significant

The likelihood that a relationship is caused by something other than chance.

Practical significance

Whether the observed effect is large enough to be useful in the real world.

Standard deviation

A measure of how spread out numbers are in a data set.

Correlation coefficient

A number between -1 and +1 that represents the linear dependence of two variables.

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