Introduction to jamovi
4h 42mGeneral2019-03-22
Authors
Barton Poulson
Professor, Designer, Data Analytics Expert
Course details
jamovi is a free, open-source data analysis application that bridges the gap between the freedom and power of R and the accessibility of SPSS. In this course, learn how to do data analysis that's both fast and friendly with jamovi. Instructor Barton Poulson demonstrates how to install jamovi and third-party modules, import and wrangle data, create visualizations based on ggplot2, and analyze data using advanced methods. Plus, see how to share your work with unified files and collaborate with the Open Science Framework (OSF).
Learning objectives
Navigating jamovi
jamovi modules
Entering and importing data
Working with box, dot, and bar plots
T-tests
Analysis of variance (ANOVA)
Linear and binomial logistic regression
Log-linear regression
Exploratory factor analysis
Learning objectives
Navigating jamovi
jamovi modules
Entering and importing data
Working with box, dot, and bar plots
T-tests
Analysis of variance (ANOVA)
Linear and binomial logistic regression
Log-linear regression
Exploratory factor analysis
Skills covered
jamoviData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and Tools
Concepts
Introduction
- introduction to jamovi
Getting Started
- installing
- navigating
- sample data
- sharing files
- sharing with osf
- jamovi modules
- jmv package
Wrangling Data
- wrangling data - chapter overview
- entering data
- importing data
- variable types and labels
- computing variables
- computing z-scores
- transforming scores to categories
- filtering rows
Exploration
- exploration - chapter overview
- descriptive statistics
- histograms
- density plots
- box plots
- violin plots
- dot plots
- bar plots
- exporting tables and plots
T-tests
- t-tests - chapter overview
- independent samples t-test
- paired samples t-test
- one-sample t-test
ANOVA
- anova - chapter overview
- anova
- repeated measures anova
- ancova
- mancova
- kruskal-wallis test
- friedman test
Regression
- regression - chapter overview
- correlation matrix
- linear regression
- variable entry
- regression diagnostics
- binomial logistic regression
- multinomial logistic regression
- ordinal logistic regression
Frequencies
- frequencies - chapter overview
- binomial test
- chi-square goodness-of-fit
- chi-square test of association
- mcnemar test
- log-linear regression
Factor
- factor - chapter overview
- reliability analysis
- principal component analysis
- exploratory factor analysis
- confirmatory factor analysis
Conclusion
- next steps