# PSY2 – Research Methods: Lesson 26

## Probability, Significance and Type Errors Teachers or students who want the original PPT or resources referred to please tweet @psychopepper

### Learning Objectives

• To KNOW and UNDERSTAND what probability and significance is in Psychology.
• To KNOW and UNDERSTAND what type errors are in Psychology.
• To APPLY knowledge of aims to past exam questions

### Lesson Outline:

1. What is the probability of drawing an ace of hearts from a pack of cards?
2. What is the probability that everything I have taught you this year is wrong?
3. Take notes on what probability and significance mean
4. Work out what p<0.05 means
5. Convert decimals to fractions
6. Discuss and take notes on what significance means in psychology and which significance levels are used when and what impact they have.
7. Discuss and take notes on type errors, finding a method of understanding that works for you. Attempt questions on type errors to check understanding.

#### Content Recap

Probability: A numerical measure of the likelihood that certain events (or behaviour) will occur

Significance: a statistical term indicating the findings are sufficiently strong for us to accept the research hypothesis and conclude the result were not by chance. The significance level that a psychologist chooses is the highest probability that their results are wrong that they are willing to accept. If I choose p≤0.05 then I am willing to accept a 5% chance that my results are wrong (due to chance). If I choose p≤0.01 then I am only willing to accept a 1% chance that my results are wrong (due to chance). And if I choose a p≤0.10 then I am willing to accept a 10% chance that my results are wrong (due to chance)

A type one error is a correct assumption that is mistakenly rejected, therefore rejecting the null hypothesis when is true. It is a false POSITIVE; and P has single vertical line… A Type I error can be viewed as the error of excessive trust. Another way of thinking about it is that an investigator may be “crying wolf” (raising a false alarm) without a wolf in sight (H0: no wolf).

A type two error is a false assumption that is mistakenly accepted, therefore accepting the null hypothesis when is false. It is a false NEGATIVE; and N has double vertical lines… A Type II error can be viewed as the error of excessive doubt. Another way of thinking about it is that an investigator may fail to “cry wolf” (doesn’t raise the alarm) when a wolf is really there (H0: no wolf).