Statistics lesson 1 - the sign test

Here is the presentation from today's lesson.

The key idea to take from this is that when we have quantitative data, we can use a statistical test to see how likely the results were to have happened simply by chance. This is the same thing as the chance of the null hypothesis being true given what happened in our experiment.

Scientists choose a 'level of significance' before starting an experiment. This is the probability of the results happening by chance alone below which they will reject the null hypothesis, and conclude that their alternative hypothesis is true. In psychology 5% (or p<0.05) is usually chosen - this means that if there is a less than 5% chance of the results happening by chance alone then the result is considered to be significant - down to whatever the effect being investigated is.

The 5% level gives a balance between the two types of error - false positives (Type I) and false negatives (Type II). Sometimes the 10% level is used - this means there is a greater chance of a false positive (saying you have found something when you haven't) but you are less likely to have a false negative (saying nothing was going on when really it was). When it's important to avoid a false positive a lower level e.g. 1% or 0.1% is used - but this means that a false negative is more likely.

Here is the 'using the sign test' homework sheet - for Thursday, along with the sign test section on the other sheet I gave out.