false negative

Terms from Statistics for HCI: Making Sense of Quantitative Data

Where there may be a real effect, but an experiment or study is not sensitive enough to detect it. Statistical power is about avoiding false negatives. A false negative conclusion is known in statistics as a Type II error. Contrast with a false positive.

Used on pages 53, 86, 87, 105