Highly specific tests minimize the occurrence of these events.
The logarithm of the probability of these events in a certain bit-array used to test for set membership is proportional to the quotient of the filter size and the number of elements in the filter. That data structure is the Bloom filter. Highly specific tests minimize the occurrence of these events. Epidemiological tests for non-life-threatening conditions that are costly to treat generally seek to minimize their occurrence. Statistical significance is a measure of the likelihood that one of these events occur, in which a Type I error is made and rejection of a true null hypothesis occurs. For 10 points, name these events in which a test incorrectly indicates that a condition is present.
The logarithm of the probability of these events in a certain bit-array used to test for set membership is proportional to the quotient of the filter size and the number of elements in the filter.
false positives [accept Type I error until it is read] &lt;AS&gt;