R 2

Linear regression, ANOVA & advanced regression models – 2 days

This course provides you with a solid understanding of modern linear regression and ANOVA models. It also covers some common but advanced regression models for dealing with categorical data and repeated measurements.

We will have a closer look at how these models work and how R can be used to build, visualise, and interpret such models. We will use modern techniques like the bootstrap and permutation tests, to obtain confidence intervals and p-values without having to assume a normal distribution for your data. We will cover non-linear regression models like logistic regression and Poisson regression, where the response variable can be either binary (yes/no), counts, or prevalence. Mixed models are used to analyse data with repeated measurements on the same subjects. We also learn about methods for dealing with missing data.

Course goals: To be able to use R to fit, visualize and interpret linear regression and ANOVA models. To understand how to visualise and interpret models for logistic regression, count regression, and mixed models. To be able to fit models with missing data.

Prerequisites: R1 or similar.

Kursinformation

R 2
Course length: 2 days
Language: English
Hours: 09:00-16:30 (CET)
Price: 12 500 SEK excluding VAT

Kurstillfällen

4-5 feb 2025
Online

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8-9 apr 2025
Online

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Förhandsbokning
(obestämt datum)

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Program

Linear regression & ANOVA

LINEAR REGRESSION
Fitting and building models
Interactions and dummy variables
Validating models
Visualizing results
Prediction

ANOVA
Fitting models
Validating models
Visualizing results

 

Advanced regression models

GENERALISED LINEAR MODELS
Logistic regression
Poisson regression and negative binomial regression
Fitting, building, and validating models

MIXED MODELS
Fixed and random effects
Linear mixed models (LMM)
Generalised linear mixed models (GLMM)

MISSING DATA
Multiple imputation

Information & Frågor

Questions?
Send us an email or Call us

Online course
All our online courses are instructor-led and on the Zoom video platform. Course literature and exercises are either distributed in conjunction with the course or delivered through mail well in advance before the course. This information and and other important instructions are found in your booking confirmation after a reservation is made.

Onsite courses
The address and any additional information is announced in an invitation email send out the week before the course. Course literature and exercise material are distributed onsite. Make sure you have access to a computer with the current program installed for the course.

Booking terms
Statistikakademin has the right to cancel any course in the event of an insufficient number of participants. In case of that happening, you will of course be offered a new course date or be fully compensated. You have the right to rescedule and change course dates up to 15 days before the start of the course. If something comes up last minute and you are not able to attend, you can of course send a colleague instead.

Kursledare

Måns Thulin

Appreciated educator with extensive statistical expertise

Måns Thulin works as a consultant and lecturer in statistics, machine learning, and artificial intelligence. His clients include large corporations, government agencies, startups, and researchers. By using advanced statistical analysis, he has solved problems in a wide range of areas, from antibiotic resistance to nuclear fuel, from milking robots to HR issues, from herniated discs to music videos. He has twelve years of teaching experience at institutions such as Uppsala University and the University of Edinburgh. Måns is also the author of the popular textbook Modern Statistics with R. His educational goal is to help all course participants understand statistical methods – statistics should feel logical, not like black magic.

Köp flera kurser samtidigt och få rabatt!

Boka flera datum själv, köp kurser och ha innestående eller gå tillsammans med en kollega.

2 kurser

10%

På båda kurserna

3 kurser

15%

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4 kurser

20%

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