What do you need to know? Introduction to the use of inferential statistics: the Sign Test What inferential tests allow us to do (that descriptive stats don’t). What the Sign test does What we use probability for

Inferential statistics Inference = a judgement based on probability Inferential Statistics allow us to - make an inference about our data.  - choose the best hypothesis Psychologists have to decide whether to accept or reject their hypothesis. How big a difference/correlation do you have to have to confidently accept your hypothesis??

Probability – the toss of a coin Chance of getting ‘heads’: Once: ½ = 50% Twice: ½ x ½ = 25% Three times: ½ x ½ x ½ = 12.5% Four times: ½ x ½ x ½ x ½ = 6.2% Five times: ½ x ½ x ½ x ½ x ½ = 3.1% Six times: ½ x ½ x ½ x ½ x ½ x ½ = 0.16% How many times would you have to get ‘heads’ in a row before you decide the coin is weighted?

How much probability of a fluke? 0% 100% If there is little chance of a fluke, then there’s a big chance it was caused by your IV.

What level of Significance? Agreed safe limit is 5% probability of a fluke. Thus, 95% probability of an effect from your IV. Below this limit is considered poor practice. (…though it could mean we reject some effects that are actually there).

How do we express it? When talking about probability, we turn the percentage into a decimal. 5% = 0.05 Probability of no more than 5%  p ≤ 0.05

Checking our stats test result Once we’ve done our stats test, we check the probability of getting that result by chance. We use critical values (worked out by the mathematicians for us!) For sign test, our figure must be equal to or less than the critical number to be statistically significant.

Sign Test: Work out Calculated Value (S) Complete the activity sheet and calculate (S) positive + negative - equal = (If you have any equal scores, ignore them and adjust the number of pp’s down)

Steps to work out Critical Value Choose level of significance (use p<0.05 Work out the number of pp’s (N) Find the right critical value (C) on the purple table on p198 N.B. a 1-tailed hypothesis is directional, 2-tailed is non-directional. (Note: sign test is only possible on repeated measures designs)

Add up number of pluses and number of minuses Less frequent sign is the S value If calculated value (S) is less than or equal to the critical value (C), we reject the null hypothesis and accept the alternate hypothesis

So what do I need to know? What inferential tests allow us to do (that descriptive stats don’t). What the Sign test does What we use probability for