DATA2002 - HD (91) Detailed Notes

Description

Included are 37 pages of detailed and concise notes that cover everything you need to know to achieve a high distinction in DATA2002. The notes are a combination of lecture content, key tutorial information, learnings from quizzes, as well as my personal breakdowns of confusing concepts. These notes were key to me achieving an HD and by studying them I believe anyone can achieve at least a distinction. I am now doing a data science internship and continue to refer to them. Topics Included: Module 1: Categorical Data - Collecting Data - Chi-Square Goodness of Fit - Measures of Performance - Measures of Risk - Testing for Homogeneity - Testing for Independence - Testing in Small Samples Module 2: Testing Means - T-Tests - Critical Values, Rejection Regions, Confidence Intervals - Sample Size Calculations and Power - Sign Test - Wilcoxon Signed-Rank Test - Wilcoxon Rank-Sum Test - Permutation Testing - Bootstrapping Module 3: Multiple Factor (ANOVA) - Multiple Testing - ANOVA - ANOVA Contrasts - ANOVA Post Hoc - When ANOVA Assumptions Fail - Two Way ANOVA Module 4: Learning and Prediction - Simple Linear Regression - Multiple Regression and Model Selection - Multiple Regression Prediction and Performance - Logistic Regression