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README.md
stroopdata.csv

README.md

DAND-Project-1---Test-a-Perceptual-Phenomenon

DAND Project 1 - Test a Perceptual Phenomenon as part of learning GitHub Desktop

Project Overview In this project, you will investigate a classic phenomenon from experimental psychology called the Stroop Effect. You will learn a little bit about the experiment, create a hypothesis regarding the outcome of the task, then go through the task yourself. You will then look at some data collected from others who have performed the same task and will compute some statistics describing the results. Finally, you will interpret your results in terms of your hypotheses.

If you need a refresher on statistics, you can take Udacity's free Statistics course.

Why this Project? Statistics is a major component of data analysis, it allows you to investigate data and make inferences based on your observations. A foundation in statistics also allows you to be a consumer of analyses that others perform, and allows you to relate to the conclusions others have drawn from their investigations.

What will I Learn? This project will review the basic concepts of statistics, including:

How to identify components of an experiment How to use descriptive statistics to describe qualities of a sample How to set up a hypothesis test, make inferences from a sample, and draw conclusions based on the results Why is this Important to my Career? Using statistics to draw valid conclusions about data is an important part of a Data Analyst's work. A strong grasp of statistics will also be necessary in the rest of the Nanodegree program.

Project Instructions Follow these instructions and create a pdf or html document answering the questions. These document formats are compatible across a broad range of computers and browsers and are one of the surest ways of making sure that your intents are received properly. If you are using a word processing program such as Microsoft Word or LibreOffice, make sure that you save your document as a pdf and include the pdf in your project submission.

There is no need for specific software for this project, but we encourage you to use Jupyter Notebook workspace in the next section to complete the project using Python.

Project Submission Use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Give your readers a good intuition for the data and use statistical inference to draw a conclusion based on the results. Use the Statistics Placement Advisor to determine if reviewing any of the Statistics course will help you prepare for this project.

Evaluation Once you have a document answering the questions on the previous page, be sure to check through the project rubric before you submit your report. Your project will be evaluated as “meets specifications” only if it meets specifications in all the criteria. If you see any category where you do not meet specifications, make sure you revise your report to meet the rubric criteria.

Submission Ready to submit your project? Collect the following files:

Answers to the questions in the instructions in a pdf or html document. A list of websites, books, forums, github repositories, and other resources (web or otherwise) that you referred to or used in this submission. This can be attached to the bottom of your answers document or placed in a separate plaintext file. (Optional) Any code or other documents that you used to compute statistics for completing the project tasks. With these materials, go to your Udacity Home page, click on this project, and follow the instructions to submit:

If you want to submit your files through a "Link to Project", upload your project files onto Github and send us the link. If you instead want to submit your files through "Upload a Zip", compress your project directory, and submit that zip file. It can take us up to a week to grade the project so keep checking back for updates.

If you are having any problems submitting your project or wish to check on the status of your submission, please email us at dataanalyst-project@udacity.com.

What's Next? You have a few projects under your belt already! You should talk about them! Communicate these newfound skills on networking platforms like LinkedIn, where you can surface to recruiters who perform daily boolean searches for potential job candidates.

A tip from Udacity's Student Talent Advocate, Mark Gentry:

"For most Silicon Valley recruiters, LinkedIn is the most important job candidate profile. You need to make sure your profile shows up in a boolean searches; to do so, your job and project descriptions need to have keywords. Take 5 minutes and make sure your LinkedIn profile checks all the boxes".

Next, get a personalized review of your LinkedIn profile by going to the Career: Networking part of your Classroom.

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