Type 1 and 2 Errors

Brief definitions of type 1 and 2 errors and model answers for 3 mark questions. Intended for OCR, Psychology A2, Unit G544: Approaches and Research Methods in Psychology.

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  • Created on: 17-06-12 09:46

Type 1 and 2 Errors

Type 1 Error

This is where a null hypothesis may be falsely rejected - the researcher may falsely claim an effect exists. This is likely to happen when a P value is too lenient such as P<0.5 or P<0.3.

Type 2 Error

This is where a null hypothesis may be falsely accepted - the researcher may falsely claim an effect does not exist. This is likely to happn when a P value is too stringent such as P<0.01.

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Type 1 and 2 Errors Using Pants

Type 1 Error

A type 1 error means your pants (null hypothesis) are too loose (lenient) as such they fall down. Therefore you reject your pants and choose a different pair (alternative/experimental hypothesis).

Type 2 Errors

A type 2 error means your pants are too tight (stringent) and so they stay up. Therefore you accept your pants (null hyopthesis).

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Type 1 Error 3 Mark Model Answer

Type 1 Error

Explain what it would mean if you had made a type 1 error when making a conclusion in relation to your null hypothesis (3 marks).

A type 1 error is where the null hypothesis is rejected falsely. In this study this would mean that I would falsely reject the null hyopthesis (insert null hyopothesis) and accept the alternative/experimental hypothesis, suggesting that there is a difference (insert IV) on the DV (insert DV). This may be due to a probability level set at a too lenient level, e.g, 10%.

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Type 2 Error 3 Mark Model Answer

Type 2 Error

Explain what it would mean if you had made a type 2 error when making a conclusion in relation to your null hypothesis (3 marks).

A type 2 error is where the null hypothesis is falsely accepted. In this study this would mean that I would falsely accept the null hyopthesis (insert null hyopothesis) and reject the alternative/experimental hypothesis, suggesting that there is a difference (insert IV) on the DV (insert DV). This may be due to a probability level set at too stringent a level, e.g, P<0.01.

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