Compute test-score statistical significance using control-scores from shuffled population

Question

[Bade]

I am not a statistician therefore need your help in computing statistical significance of my data. Suppose I have 2 baskets (B1 and B2) on a table each with mix of apple and oranges, and there are 10 such tables (T1 to T10. Now, I have computed the log-odd score of finding apples in B1 at all 10 tables:

2.95    5.56    6.025   7.225   7.37    7.39    7.54    7.54    6.82    7.295

To generate a control population I (randomly) shuffled fruits between B1 and B2 on every table, keeping the number of fruits in each basket same as above. And again computed generalized log-odd score of finding apples in B1 at all 10 tables:

scores from shuffled control-1
0.81    1.25    0.695   0.725   -0.23   -0.25   -0.27   0.2 0.04    0.035

scores from shuffled control-2
-0.81   0.94    0.855   0.41    0.37    0.755   0.78    0.78    -0.075  0.59

and 3 more iteration, so total 5 different iterations with shuffled scores.

How can I compute p-values representing statistical significance of log-odd scores from real (B1) baskets against shuffled (control)baskets, for each table? And can I do so in R, because I have 100 or more such tables?

Thanks

Bade

[Nicolas Rosewick]

replicate() function will help you.

Answer 1

[mastal511]

Yes, R is very good for that sort of analysis.