Sentence examples for affected by uncertainty from inspiring English sources

The phrase "affected by uncertainty" is correct and usable in written English.
It can be used when discussing situations, decisions, or outcomes that are influenced or impacted by a lack of certainty or predictability.
Example: "The company's financial projections were significantly affected by uncertainty in the market."
Alternatives: "influenced by unpredictability" or "impacted by ambiguity."

Exact(57)

A third of respondents said their business had been adversely affected by uncertainty surrounding the vote, which is likely to be tight.

Indeed, in 1983 a young American economist named Ben Bernanke published a paper* analysing how investment would be affected by uncertainty.

Analysts said other countries that have gotten help from the I.M.F., like Hungary and Ukraine, could also be affected by uncertainty over Latvia, raising the prospect of renewed financial turbulence in emerging markets.

The statement suggested the faltering growth was affected by uncertainty in the City and money markets, noting that financial advertising "continues to be weak" while retail and travel categories had performed well.

He said that shoppers had also been affected by uncertainty around the EU referendum since January this year, and consumer confidence continued to be affected by concern about what Brexit might mean for household finances.

John Walden, the chief executive of Argos's parent Home Retail Group, said he did not believe trading at Argos had been affected by uncertainty around the takeover but was the result of a difficult market for electrical goods, which make up more than half of the chain's sales.

However, such sensors are commonly affected by uncertainty.

Both research and innovation are essentially affected by uncertainty and indeterminacy.

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Similar(3)

Such a quantity is expected to be less affected by uncertainties of radiometric calibration.

The location procedure is intrinsically affected by uncertainties associated with different causes.

These models are affected by uncertainties, therefore robustness is of primary importance.

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