Overview
This lecture provides a comprehensive introduction to Jamovi, a free, user-friendly data analysis tool based on R, covering installation, data management, statistical analyses, visualizations, collaboration, and next steps for developing data skills.
Introduction to Jamovi
- Jamovi is a free, open-source data analysis software built on R, designed for ease of use.
- Mimics SPSS interface but uses the R backend, making it accessible for both beginners and those transitioning from other software.
- Runs on Windows, Mac, and Linux; install from the Jamovi website.
Getting Started and Navigation
- The interface features a single window: data goes on the left (spreadsheet layout), results/output on the right.
- Main menus: Analysis (statistical procedures), Data (variable setup & editing), and Files (open, save, import).
- Sample datasets are included for practice (Big Five, Tooth Growth, Bugs, Iris).
Data Management in Jamovi
- Data can be entered manually but is best imported from spreadsheets (CSV, TXT) or statistical software files (SPSS, SAS).
- Define variables by type (continuous, ordinal, nominal), add labels, and manage levels/categories for clarity.
- Compute new variables (e.g., averages, z-scores) using built-in functions.
- Transform variables and apply saved transformations across datasets.
- Filter cases to focus analyses on subsets of data.
Data Exploration & Visualization
- Explore data with descriptive statistics (mean, SD, frequencies) and visualizations (histograms, density plots, box plots, violin plots, dot plots, bar charts).
- Data and output can be exported to Word, Excel, Google Docs, or as images/PDFs for presentations.
Statistical Analyses
- T-tests: supports independent, paired samples, and one-sample t-tests for inferential statistics.
- ANOVA: covers factorial ANOVA, repeated measures, ANCOVA, MANOVA, and non-parametric alternatives (Kruskal-Wallis, Friedman).
- Regression: linear, binomial logistic, multinomial logistic, and ordinal logistic regression for prediction and classification.
- Frequency analysis: binomial tests, chi-square tests (goodness-of-fit, association), McNemar’s test, log-linear regression.
Factor Analysis & Scaling
- Reliability analysis assesses internal consistency (e.g., Cronbach’s alpha) for scales.
- Principal component analysis (PCA) and exploratory factor analysis (EFA) identify underlying variable structure.
- Confirmatory factor analysis (CFA) tests hypothesized factor models.
- Modules extend functionality for specialized analyses.
Collaboration & File Sharing
- Analyses are saved in a single .omv file containing data, transformations, and results.
- Files can be shared via email or cloud storage; Open Science Framework (OSF) integration supports reproducible collaboration.
R Integration & Syntax
- Syntax mode displays the R commands generated by Jamovi, bridging menu-driven and code-driven workflows.
- Users can copy Jamovi-generated R code for use in R or RStudio.
Key Terms & Definitions
- Jamovi — Free, open-source data analysis software based on R.
- Variable Type — Describes measurement level: continuous (quantitative), ordinal (ordered categories), nominal (named categories).
- Transformation — Operation applied to create a new or modified variable.
- Modules — Add-on packages extending Jamovi’s analysis capabilities.
- Descriptive Statistics — Summarizes data (mean, SD, frequencies).
- Inferential Statistics — Tests hypotheses about populations using sample data (e.g., t-test, ANOVA).
- Regression — Predicts outcomes using one or more variables.
- Factor Analysis — Identifies underlying patterns or constructs in sets of variables.
Action Items / Next Steps
- Download and install Jamovi from jamovi.org.
- Access course files and sample datasets from DataLab.cc/tools/jmv.
- Practice importing, defining, and analyzing your own or provided sample data.
- Explore Jamovi modules for additional techniques if needed.
- Consider learning basic R syntax to extend your analysis skills.
- Work on real data projects and improve your data fluency and interpretation skills.