Full ETC1000 Exam Notes | 90HD

Description

One of the things I have observed that other students often neglect is clearly defining terms and finding clear connections between them. This is the approach off of which these notes are based. The notes are detailed, as well as relevant and specific to the course. The understanding is clearly outlined as a result of questioning TAs and searching the Internet for concise explanations so that you won't need to do the searching yourself. The wording aligns with what the unit has taught is correct exam practice. ETC1000 covers 8 topics: 1. Categorical data & probability (eg independence) 2. Numerical data (eg histograms, normal distributions) 3. Patterns in data (eg correlation, covariance) 4. Uncertainty (eg confidence intervals, z-values) 5. Hypothesis testing (eg hypotheses, significance level) 6. Multiple linear regression (eg the multiple linear regression model) 7. Prediction (eg time-series graphs, modelling) 8. Business modelling (eg optimisation)