Introduction to Inferential Testing
Psychology: AQA A Level, topic 7.4.1
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.
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.
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.
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.
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.
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.
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).
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.
Test yourself on Introduction to Inferential Testing
What's the most common level of significance in psychology?
Which of these are true of type I errors?
Complete the information about type II errors.
What type of hypothesis is this?
'Drinking coffee after 3pm will disrupt sleep patterns'