Emerging Technology Tasks

A variety of tasks provided to me by my lecturer Ian McLoughlin.

Task 1 -- Square Root of 2

In this task we were told to get the square root of 2 to 100 decimal places without importing anything to aid us. After researching I found and used the Digit-by-digit calculation in order to help calculate the square root of 2 accuratly to 100 decimal places.

Task 2 -- Chi² testing

Chi² testing is a statistical hypothesis test simlar to a t-test. It's used to check if two different categories are independent/dependent of eachother In this task we were given a table from wikipedia which had a Chi-squared value of approximately 24.6. We had to use scipy.stats to verify that was indeed the correct value.

I succesfully determined that 24.6 was correct and also learned that that A & B are not independent of each other ,similarly for C & D. Meaning that A & B and C & D are from the same sample populations.

Task 3 -- Standard Deviation

For this task we were required to find the sample standard deviation and popluation standard deviation of a number and determine what was more accurate. Ultimatly the sample standard deviation is more accurate as with the popluation standard deviation , its very difficult to collect a sample from a large population.

Task 4 -- Fisher’s Iris data set

For the final task we were asked to use scikit-learn to apply k-means clustering to Fisher’s famous Iris data set.

I used machine learning to estimate which flower was which in the graph by using the sepal length and width of the flowers.

To view the tasks for more detail ,please view Emerging Technology - Tasks.ipynb

Getting Started

• Download the latest version of python
• Download the latest version of jupyter Notebook
• Run on jupyter notebook by entering comand prompt in the project directory and enter "Jupyter Notebook"

Built With

• jupyter Notebook - The text editor
• Python - Language Used

Authors

• Blaine Burke - GitHub

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• Ian McLoughlin - Provided the tasks to be completed
• Stackoverflow - Proved helpful with bug fixes and for research
• wikipedia - Provided helpful articles and information on some of the algorithms used