7.4.1

Introduction to Inferential Testing

Test yourself

Inferential Testing

The aim of inferential statistics is to discover if your results are statistically significant. A statistically significant result is one which is unlikely to have occurred through chance.

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Null hypothesis

  • Usually, psychologists use the 5% level (0.05). This means that just 1 in 20 of results could have occurred due to chance.
  • We express our results in terms of the null hypothesis. If a result is statistically significant, we can reject the null hypothesis. If the result is not statistically significant we must accept the null hypothesis.
  • In other words, we need to be 95% confident that the results were due to the manipulation of the IV in order to reject the null hypothesis.
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Common level of significance

  • In psychology, the most common level of significance is 5% (e.g. 1 in 20 or p≤0.05) (the p stands for probability and ≤less than or equal to).
  • This level is seen as a representing a balance between a type I and type II error.
  • The 5% level is fine for psychology, but clearly if we were experimenting on a new drug, a 1 in 20 chance that it might kill you are not very good odds and the level would have to be significantly reduced.
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Type I error

  • False positive.
  • Rejecting the null hypothesis, when there is a possibility that the results were due to chance.
  • Often caused by using a significance level that is too lenient e.g. 10%, 0.10, 1 in 10, p≤0.10. Not being cautious enough.
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Type II error

  • False negative.
  • Accepting the null hypothesis, when there is a possibility that the results were significant.
  • Often caused by using a significance level that is too strict e.g. 1%, 0.01, 1 in 100, p≤0.01. Being over cautious.
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Critical value table

  • Once an inferential statistical test has been carried out, it is necessary to compare the calculated value against the critical value in a critical value table to see if the result is statistically significant and the null hypothesis can be rejected.
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Exam question

  • A common question in the examination is to interpret a result using critical value tables, therefore make sure you have practiced this.
  • You will need to know if the study used a 1 or 2 tailed hypothesis (directional or non-directional). The significance level is generally 0.05.
  • For most tests, N = number of participants, however for Chi-squared you will need to calculate the degrees of freedom (df).
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Directional vs non-directional hypothesis

  • A directional hypothesis says that the independent variable will have an effect on the dependent variable. It will state what that effect will be (in other words, the direction of results).
    • E.g. Eating cheese before bed will disrupt a person's sleep.
  • A non-directional hypothesis just says that the independent variable will affect the dependent variable BUT it does not predict how the IV will affect the DV.
    • E.g. Eating cheese before bed will affect a person's sleep.

Jump to other topics

1Social Influence

2Memory

3Attachment

4Psychopathology

5Approaches in Psychology

6Biopsychology

7Research Methods

8Issues & Debates in Psychology (A2 only)

9Option 1: Relationships (A2 only)

10Option 1: Gender (A2 only)

11Option 1: Cognition & Development (A2 only)

12Option 2: Schizophrenia (A2 only)

13Option 2: Eating Behaviour (A2 only)

14Option 2: Stress (A2 only)

15Option 3: Aggression (A2 only)

16Option 3: Forensic Psychology (A2 only)

17Option 3: Addiction (A2 only)

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