In this project, I investigated a classic phenomenon from experimental psychology called the Stroop Effect. I created a hypothesis regarding the outcome of the test, looked at data collected on the actual outcome of the test and computed statistics describing the results. Ultimately, I interpreted the results in terms of my hypothesis.
- Identify components of an experiment
- Use descriptive statistics to describe qualities of a sample
- Set up a hypothesis test, make inferences from a sample and draw conclusions based on the results
Create a Python environment in Jupyter Notebook with the following packages:
Find any typos? Have another resource you think should be included? Contributions are welcome.
First, fork this repository.
Next, clone this repository to your desktop to make changes.
$ git clone https://github.com/ccaddel/stroop_effect.git
$ cd stroop_effect
Once you've pushed changes to your local repository, you can issue a pull request by clicking on the green pull request icon.
Instead of cloning the repository to your desktop, you can also go to README.md in your fork on github.com, hit the Edit button (button with the pencil) to edit the file in your browser, then hit the Propose file change button, and finally make a pull request.