Type I errors in statistical tests represent false positives where a true null hypothesis is falsely rejected Type II errors represent false negatives where we fail to reject a false null hypothesis For a given experimental system increasing sample size will A decrease both Type I and Type II errors B decrease Type I and increase Type II errors C increase both Type I and Type II errors D increase Type I and decrease Type II errors

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Type-I errors in statistical tests represent false positives, where a true null hypothesis is falsely rejected. Type-II errors represent false negatives where we fail to reject a false null hypothesis. For a given experimental system, increasing sample size will (A) decrease both Type-I and Type-II errors (B) decrease Type-I and increase Type-II errors (C) increase both Type-I and Type-II errors (D) increase Type-I and decrease Type-II errors

Asked On2019-07-09 04:13:16 by:KAPILJHADE

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