EDX-MITx: 6.00.2x Introduction to Computational Thinking and Data Science
###quiz:
- Problem 5-1.py - Write a function called sampleQuizzes that implements a Monte Carlo simulation that estimates the probability of a student having a final score >= 70 and <= 75.
- Problem 5-2.py - Write a procedure called plotQuizzes that produces a plot of the distribution of final scores for all of the trials. Try your best to match exactly how the histogram below looks (including the bins, titles and labels on the axes). Click the image to see a larger version.
- Problem 6-3.py - You observe that the probability of first seeing a 1 on the n-th roll decreases as n increases. You would like to know the smallest number of rolls such that this probability is less than some limit.
###PS6 Machine Learning
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In this problem, you will implement three different linkage criteria: singleLinkageDist, maxLinkageDist, and averageLinkageDist. For our purposes, distances between elements will be calculated using the Point class distance method, which calculates the Euclidean distance.
The singleLinkageDist between two clusters is the shortest distance between an element in one cluster to an element in the other cluster. In other words, the distance will be that between the points that are closest to each other, where one point is from one cluster and the other is from the other cluster. The maxLinkageDist between two clusters is the largest distance between an element in one cluster to an element in the other cluster. In other words, the distance will be that between the points that are farthest from each other, where one point is from one cluster and the other is from the other cluster. The averageLinkageDist between two clusters uses the mean to find the average distance between all possible pais of elements (p1, p2) where p1 is from one cluster and p2 is from the other cluster.