The purpose of this project is to investigate the Stroop Effect using a dataset provided by Udacity. This project was completed as part of the Udacity Data Analyst Nanodegree program.

In a Stroop task, participants are presented with a list of words with each work displayed with a color. The participant has to say out loud the color of the ink in which the word has been written. The task has two conditions: Congruent and Incongruent.

Congruent words are displayed as the word of the color of which they are written in. For example, RED would be written using red ink.

Incongruent words are displayed in a different color of which they are written in. For example, RED would be written in any other colors apart from red.

We want to prove there is no difference in time taken to complete congruent and incongruent tasks. So therefore, our null hypothesis stats that the difference between the population mean for incongruent tasks will be less than or equal to zero compared to the congruent population mean times

You can view the analysis by looking at the Jupyter Notebook file or by examining the html file output.

In this project, I implemented the following Python libraries:

• Pandas
• Numpy
• Matplotlib.pyplot
• Scipy