A Type I statistical error occurs when a researcher claims that there is not enough support to establish significance for the research hypothesis, but in fact there is enough.

The statement describes a Type II error: the researcher fails to find enough support for the research hypothesis even though it is true. A Type I error is the opposite kind of mistake—finding support for an effect when there is no real effect. So the statement is false.

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