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Psych/Lab2.1 is a set of programs for running versions of classic experiments from Human Cognitive/Experimental Psychology. The programs were created using the open source (i.e. free!) experiment-generation application PsychoPy. PsychoPy is a good alternative to programs such as e-Prime or Superlab. The source files for all of the experiments are provided. These can be easily modified to accommodate desired variations in the experiments, and they also serve as good examples for those who want to learn how to use PsychoPy to create their own experiments. Data are saved in Excel files and can be easily analyzed.  (See the instructions below for creating pivot tables in Excel.)


Download Psych/Lab here.

Download PsychoPy here.
(Note that Psych/Lab has been tested with version 1.85.2 of PsychoPy.  You should probably download that version.  After installing PsychoPy, in the PsychoPy preferences, on the General tab, change the window type to pyglet.)

Learn how to use PsychoPy with our Simon Effect tutorial.


Data analysis in Excel

It is fairly easy to analyze data from all of the Psych/Lab programs in Excel.  The most efficient way to do that is through the use of Pivot tables, which are explained here.

Double-click on the *.CSV data file created by the experiment program.

In many experiments the initial rows will contain practice trials.  Delete those (but don’t delete the labels in the first row).

Highlight the entire table (by clicking on the box above and to the left of cell A1).

Select the INSERT tab.  Click PIVOT TABLEthen click OK.

In the pivot table field list:

1.       Drag condition to the column labels box.

2.       Drag keyresponse.rt to the values box.

3.       Drag keyresponse.rt to the values box again.

4.       In the values box, click one of the keyresponse.rt entries and change the value field setting to Average.

5.       Drag the Σ Values from the Column labels box to the row labels box

6.       Drag keyresponse.corr to the report filter box.

7.       At the top of the pivot table, select the drop-down menu for the keyreponse.corr filter and select the value 1 (these will include only correct trials in the table).


Experiment by adding additional experiment design variables to either the column labels or row labels boxes.  This will allow you to view means of your dependent variable separately for different levels of some of those factors.



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Fall 2017:
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