Mathematical Statistics: Linear and Logistic Regression

Education facts

Code: MASM22

<p>How can we explain and quantify the effect of underlying variables on the probability of an event?</p><p>Least squares and maximum-likelihood-method; odds ratios; Multiple and linear regression; Matrix formulation; Methods for model validation, residuals, outliers, influential observations, multi co-linearity, change of variables; Choice of regressors, F-test, likelihood-ratio-test; Confidence intervals and prediction. Introduction to: Correlated errors, Poisson regression as well as multinomial and ordinal logistic regression.</p>

Entry requirements

60 ECTS credits, and knowledge corresponding to MASA01 Mathematical Statistics: Basic Course, 15 credits, MASB02 Mathematical statistics for chemists, 7.5 credits, MASB03 Mathematical statistics for physicists, 9 credits or MASB11 Biostatistics - basic course, 7.5 credits (i.e. an introductory course in mathematical statistics). English 6/English Course B.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Mathematical Statistics: Linear and Logistic Regression

  Lund University

  Lund

  Start date: 29 March 2027

  End date: 6 June 2027

  Pace of study: 50 %