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 Type I and Type II Error  

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What is the probability of making a type I error?
what is the prob. of making a type II error?


Which is worse?


The probability of making type I erroris alpha,P<0.05. The probability of making type II error is



The probability of making type I erroris alpha,P<0.05. The probability of making type II error is



Type I error generally represents False negative,that is as P becomes less than 0.05 the false negative are going to be decreased.In the same way in Type II error the power of the test is denoted by 1- Beta.the power represents the true negatives where as beta represents the false positives.hence a balance should be struck so that there is a balance between them.but most clinical research studies P less than 0.01.hence as cut off point is very low the alpha error is decreased but there is a chance of increased beta error,that is false pos.. are increased.and vice versa occurs.hence balace should be struck between the two.

hope Iam clear about it


I think alpha error is worse. It's like saying a drug does produce a clinically significant when in fact it does not..(Like a Lie). A type 2 error is like saying a drug does not work when it fact it does have therapeutic significance. ??? I think this is it..correct me if i'm wrong.


You all are right. The probability of making a type I Error is alpha or The probability of making a type II Error is Beta. Beta=1-Power.

Now whats the answer to this Q? and WHY???

8. A group of researchers mistakenly conclude from a poorly designed experiment that acetaminophen cures the common cold. They have committed which of the following?<?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />

A. 1-&beta; error

B. Alpha error

C. Beta error

D. Type I error

E. Type II error


Type II error,because they have would taken alpha very less hence more chance of type II error


i think alpha error


ans:type 1 error

alpha is the probability of making type one error .


The correct answer is D. Type I errors occur when researchers reject the null hypothesis when they should not have. In other words, they conclude a significant result when in actuality it does not exist. This is a particularly dangerous error to make, as it could lead to the administration of an ineffective drug to patients in need of life-preserving treatment. <?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />

Thanks everyone.
To conclude:
Type I error is worse
alpha is the probability of making a type I Error.
Type II error = 1-Power
(Type II error (beta error) does NOT equal alpha!)


Very good Dr. Virgo, because the definitions of both may appear as "double talk" to many". But in inactuality this is a significant part of biostat and epidemiolgy.




Is Type I error the same as alpha error?
Where is this question coming from? I assume that is not from actual USMLE exam, or from NBME.

Alpha = I = False Positive (in reality it is false, but was mistakebly accepted by study as truth, a bad drug but shown as a good one = LIE)
ONLY if we reject H(0) but must not - alpha(I) error
ONLY Rejecting H(0) we could make alpha(I) error with chance 5% (5 from 100, 1 from 20) if p=0.05

Beta= II = False Negative (in reality it is truth, but was rejected, a good drug but shown as a bad one = MISTAKE)
ONLY if we accept H(0) but must not - beta(II) error
ONLY Accepting H(0) we could make beta(II) error with chance 1-Power (p=0.05 does not matter)

LIE(I) is worst then MISTAKE(II)


STUDY SHOW TRUTH (+)---------TP-------------------FP(I)alpha

STUDY SHOW FALSE (-)-------FN(II)beta---------------TN

TP=POWER= 1 - beta




alfa or type 1 error is actually false positive!!

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