Rubbing & Scrubbing My Data

by Kristin Sainani CONTENTS 1. Descriptive statistics and looking at data 2. Review of study designs; Measures of disease risk and association 3. Probability, Bayes' Rule, Diagnostic Testing 4. Probability distributions 5. Statistical Inference 6. P-values (errors, statistical power, and pitfalls) 7. Statistical Tests 8. Regression Analysis 9. Logistic Regression, Cox Regression 1. Descriptive statistics and looking at data 1.1 Types of Data 1.1.1 Quantitative Variable It is a numerical data(e.g., Age, Blood pressure, BMI, Pulse) that you can add, subtract, multiply, and divide. ㆍ Continuous (quantitative) variable: can theoretically take on any value within a given range (e.g., height=68.99955... inches) ㆍ Discrete (quantitative) variable: can only take on certain values (e.g., count data) However, In the real world, sometimes the distinction between continuous and discrete actually doesn't make much difference. For example, when we analyze a family size from discrete value(e...

By Andrew Ng 1. Logistic Regression      1.1   Visualizing Data Part             └ plotData function     1.2   Advanced  Optimization  Part             └ mapFeature function             └ costFunctionReg function             └ fminunc function         1.3   Decision Boundary and Prediction   Part             └ plotDecisionBoundary function             └ predict function 1. Logistic Regression We'll implement regularized logistic regression to predict whether microchips from a fabrication plant passes quality assurance (QA). During QA, each microchip goes through various tests to ensure it is functioning correctly. Suppose you're the product manager of factory and you have the test results for some microchips on two different tests. From...

by ChengXiang Zhai CONTENT 1. Overview Text Mining and Analysis 2. Natural Language Processing & Text Representation 3. Word Association Mining and Analysis      └ Paradigmatic      └ Syntagmatic 7. Topic Mining and Analysis 8. Probabilistic Topic Models 9. Probabilistic Latent Semantic Analysis (PLSA) 10. Latent Dirichlet Allocation (LDA) 11. Text Clustering 12. Text Categorization 13. Opinion Mining and Sentiment Analysis 14. Latent Aspect Rating Analysis 15. Text-Based Prediction 16. Contextual Text Mining 3. Word Association Mining and Analysis 3.1 Paradigmatic Relation Discovery ㆍParadigmatic Relation A & B have paradigmatic relation if they can be substituted for each other (i.e., A & B are in the same class) 3.2. Syntagmatic Relation Discovery In semiotics, syntagmatic analysis is analysis of syntax or surface structure (syntagmatic structure) as opposed to paradigms (paradigmatic analysis). This is often achieved using commutation tests....