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Lund University

Mathematical Statistics: Linear and Logistic Regression

<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, ch…

  • Higher education
  • Information unavailable
  • 23 March 2026
  • Information unavailable
  • Information unavailable
  • 50 %

Overview

<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><p>https://www.maths.lu.se/english/education/all-courses/courses-faculty-of-science/</p>

Admission scores

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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.

The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.

Source, measure and data quality
Source
Skolverket Susa-navet
Period
2026-03-23
Measure
Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
Population
Education offering e.uoh.lu.masm22.52953.20261
Last checked
2026-09-23T10:38:33.477975+00:00
Limitation
Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.

Programme content

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Study structure

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Application and important dates

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  2. Programme or course ends

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Common occupations after graduation

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Students

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Geographical background

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Previous upper-secondary schools and programmes

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About the provider

Lund University

Provider for the published education offering.

Sources and data quality

Education facts for the selected offering come from Skolverket Susa-navet.

Retrieved . Published . Times are shown in Swedish local time.

Source identity and publication version
Publication version
8e217193-f5fa-4778-b085-a4521fd03e8d
Education identity in the source
i.uoh.lu.masm22.52953.20261
Offering identity in the source
e.uoh.lu.masm22.52953.20261
Education-form source code
HS
Education code in the source
MASM22
Change time according to the source
2025-07-09T12:15:42

The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.