is this correct regarding null hypothesis and alpha errors?

[suckerfree]

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Hi,

Could anyone tell me if this is wrong because this is how I think of this confusing concept:

-------
Null hypothesis: there is no relationship between risk factor and disease state; the relationship you're trying to establish is not there.

Type I alpha error: you made a mistake to have rejected the null (error of commision)

Type II beta error: you made a mistake to have accepted the null (error of ommission)

If p < .05, you should accept the null
p = probability of commiting an alpha error; probability of being wrong to reject the null and believe there is a relationship between the risk factor and the disease

 

[superoxide]

Hi,

Could anyone tell me if this is wrong because this is how I think of this confusing concept:

-------
Null hypothesis: there is no relationship between risk factor and disease state; the relationship you're trying to establish is not there.

Type I alpha error: you made a mistake to have rejected the null (error of commision)

Type II beta error: you made a mistake to have accepted the null (error of ommission)

If p < .05, you should accept the null
p = probability of commiting an alpha error; probability of being wrong to reject the null and believe there is a relationship between the risk factor and the disease

You are correct. Here's just another way of looking at it (this is the way I remember it from FA):


Type 1 error: 'you saw something that didnt exist' .There was no relationship, but you saw one. you should have accepted the null hypothesis, but you rejected it.

Type 2 error: 'you did not see a difference that did exist' There was a relationship, but you didnt see it. You should have rejected the null hypothesis, but you accepted it.

 

[trudub]

Hi,

Could anyone tell me if this is wrong because this is how I think of this confusing concept:

-------
Null hypothesis: there is no relationship between risk factor and disease state; the relationship you're trying to establish is not there.

Type I alpha error: you made a mistake to have rejected the null (error of commision)

Type II beta error: you made a mistake to have accepted the null (error of ommission)

If p < .05, you should accept the null
p = probability of commiting an alpha error; probability of being wrong to reject the null and believe there is a relationship between the risk factor and the disease

Not quite right though. You say if p < .05 then ACCEPT the null. In fact, if p < .05 (if that is what you have set as your alpha value) then you should REJECT the null. If p < .05 that means that there is less than a 5% chance that the observed difference is by chance.