tricky data

USAGE SUMMARY

The phrase "tricky data" is correct and usable in written English.
It can be used to describe data that is difficult to interpret, analyze, or work with due to its complexity or ambiguity. Example: "The researchers encountered some tricky data that required additional analysis to draw accurate conclusions."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

Predicting the impact of conservation and rate changes turns out to be a tricky data problem.

TechCrunch

As a result, we can see that the linear function fittings have larger residuals than the parabolic cases for both assumed starting points (Removing a tricky data point at Lm = 26 changes the residual by less than 10%, and does not change this tendency).

Earth, Planets and Space

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

His syllabus reflects the issues, which include tricky questions of data manipulation and conflicts of interest.

The New York Times - Science

Section Regression to the Mean examines a particularly important and tricky issue in data analysis, regression to the mean.

Principles and Practice of Clinical Research

I think that's a little tricky because the data needs to be very targeted.

TechCrunch

Turnout data is tricky to work with.

The New York Times

"It's more tricky to get the data on social mobility.

The Guardian

Criminal prosecutions are costly and tricky, especially when the data is stolen, and may have netted even less.

The Economist

Even the most proficient software engineers and developers acknowledge that deleting that data is tricky and may require multiple steps.

The New York Times

"The issue of empty homes picks a nerve with people, but it's tricky to get the data to say anything sensible because it's often not clear why the 'homes with no usual residents' turn up," says Neal Hudson, an analyst at Savills estate agency.

The Guardian

But the "trend" rate of growth discussed by forecasters and, yes, by journalists is never as fixed as they make it seem: it can be influenced by shocks like rising oil prices or wars.This may obscure deeper relationships hidden in the data, posing tricky problems for statisticians.

The Economist

Expert writing Tips

Best practice

Before starting a data analysis, make sure that there are proper checks that can prevent any unexpected behavior from the dataset

Common error

Failing to acknowledge and address potential biases in "tricky data" can lead to skewed results and inaccurate conclusions. Always consider the source and collection methods.

Linguistic Context

The phrase "tricky data" functions as an adjective-noun combination, where "tricky" modifies the noun "data". As shown by Ludwig, it is used to describe data that presents challenges in analysis or interpretation.

Expression frequency: Rare

Frequent in

News & Media

50%

Science

50%

Formal & Business

0%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "tricky data" is a phrase used to describe datasets that are challenging to analyze or interpret due to their complexity or potential for misinterpretation. Ludwig AI confirms its grammatical correctness, and while it's not exceedingly common, its use spans across various contexts including news and science. When working with "tricky data", it's essential to employ careful analysis techniques, document all steps thoroughly, and be mindful of potential biases. More formal alternatives like "complex data" or "challenging data" can be used to maintain a level of formality, especially in academic or professional writing.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

complex data

Replaces "tricky" with a more direct synonym, focusing on the inherent complexity of the data.

difficult data

A simpler and more straightforward way to express the difficulty in handling the data.

challenging data

Emphasizes the difficulty in dealing with the data, similar to "tricky".

problematic data

Highlights the issues and potential problems associated with the data.

intricate data

Highlights the detailed and complex nature of the data, making it hard to understand quickly.

ambiguous data

Focuses on the lack of clarity and potential for misinterpretation within the data.

opaque data

Implies that the data is difficult to see through or understand, lacking transparency.

sensitive data

Implies that the data requires careful handling, often due to privacy or security concerns.

elusive data

Suggests the data is hard to obtain or interpret, implying it's not easily accessible or understandable.

unreliable data

Indicates the data may not be trustworthy or accurate, making it difficult to use.

FAQs

How can I effectively analyze "tricky data"?

Start by thoroughly cleaning and preprocessing the data. Employ robust statistical methods and visualization techniques to identify patterns and anomalies. Document your analysis process meticulously.

What are some common sources of "tricky data"?

Incomplete datasets, biased sampling methods, and poorly documented data collection processes are frequent culprits. Data from social media or poorly designed surveys can also be "tricky".

What can I say instead of "tricky data"?

You can use alternatives like "complex data", "challenging data", or "problematic data" depending on the context.

Is it appropriate to use "tricky data" in formal writing?

While "tricky data" is understandable, in formal or academic writing, using more precise terms like "complex data" or "ambiguous data" may be more suitable to convey the specific issue.