Data was coded as '1's for incorrect answers and '0's for correct answers, then averaged for each lists 'error' rate. 

Experiment 1
Per block analysis = to check for differences per block (1-5) you will need to average error rates for Hebb and filler lists for each block (five columns). This can then be analysed using a 2x5 ANOVA. 
Combined block analysis = average all Hebb and fillers, regardless of block number (1-5 only). Create a slope column for Hebb and filler lists, then perform a t-test comparing the slopes. 
Block 6 Analysis = ONLY analyse if significant learning if found in blocks 1-5. This was not analysed in our experiments. If needed though, average the 5 Hebb list error rates and the 5 filler list error rates then compare using a t-test on slopes.

Experiment 2 - the two files are in the correct format for ANOVA/t-test analysis. You can run a 2x7 repeated measures ANOVA on the initial learning data, or a t-test comparing Hebb and filler slopes (create a slope for each participant across epochs). You can run a 2x2 repeated measures ANOVA on the transfer data.

Experiment 3 - the file is in the correct format for ANOVA/t-test analysis. You can run a 2x7 repeated measures ANOVA on the main data, or a t-test on the slopes of Hebb and filler lists (create a slope for each participant across epochs)

See README (Data Information) file for specific details about each experiment, such as column names etc.