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Lesson 9: Reliability, Validity and Extraneous Variables.

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Presentation on theme: "Lesson 9: Reliability, Validity and Extraneous Variables."— Presentation transcript:

1 Lesson 9: Reliability, Validity and Extraneous Variables

2 Reliability refers to the consistency of a research study. There are two types of reliability. Reliability

3 Internal Reliability = This is whether a test is consistent within itself. External Reliability = This is whether a test is consistent over time (test-retest method).

4 If a study has validity then it is measuring what it intends to measure. There are two types of validity. Validity

5 Internal Validity = This is when the outcome of the study is a direct result of the manipulation of the IV. External (Ecological) Validity = This is the extent to which the findings of a study can be generalised to other settings.

6 There are several types of extraneous variables that researchers control for to prevent them from becoming confounding variables and affecting the validity of the study. Control of Extraneous Variables

7 Participant Variables = These are characteristics of the participants which may affect the DV (e.g. intelligence, age, gender, personality etc). Choosing an appropriate experimental design can help to try and overcome these extraneous variables, for example repeated measures and matched pairs.

8 Situational Variables = These are factors in the environment where the experiment is conducted that could affect the DV (e.g. temperature, time of day, lighting, noise etc.). The answer to this is standardisation (i.e. making sure that all the conditions, materials, and instructions are the same for every participants).

9 Experimenter Variables = These are factors to do with the experimenter which can affect the DV, for example personality, appearance, and conduct of the experimenter. Female researchers can gain very different results from male researchers.

10 Single blind technique (i.e. making sure participants do not know what the hypothesis is) can help to avoid demand characteristics. This is more difficult to accomplish in repeated measures design. The double blind technique (i.e. neither the participants nor the investigator know the hypothesis) can avoid investigator effects.


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