jamovi for Data Analysis - Full Tutorial

Dive into a comprehensive tutorial on jamovi, a free and open-source data analysis application. Learn to refine, analyze, and visualize data effectively using this intuitive tool based on the R programming language. Master essential skills including data wrangling, exploration techniques, statistical tests (t-tests, ANOVA, regression), frequency analysis, and factor analysis. Explore jamovi's user-friendly interface, import and manipulate data, create various plots, and conduct advanced statistical procedures. Gain practical experience with sample datasets and learn to share your work using OSF.io. Perfect for beginners transitioning from SPSS or those seeking a powerful yet accessible data analysis solution.

) Welcome.
) Installing jamovi.
) Navigating jamovi.
) Sample data.
) Sharing files.
) Sharing with OSF.io.
) jamovi modules.
) The jmv package for R.
) Wrangling data: chapter overview.
) Entering data.
) Importing data.
) Variable types & labels.
) Computing means.
) Computing z-scores.
) Transforming scores to categories.
) Filtering cases.
) Exploration: chapter overview.
) Descriptive statistics.
) Histograms.
) Density plots.
) Box plots.
) Violin plots.
) Dot plots.
) Bar plots.
) Exporting tables & plots.
) t-tests: chapter overview.
) Independent-samples t-test.
) Paired-samples t-test.
) One-sample t-test.
) ANOVA: chapter overview.
) ANOVA.
) Repeated-measures ANOVA.
) ANCOVA.
) MANCOVA.
) Kruskal-Wallis test.
) Friedman test.
) Regression: chapter overview.
) Correlation matrix.
) Linear regression.
) Variable entry.
) Regression diagnostics.
) Binomial logistic regression.
) Multinomial logistic regression.
) Ordinal logistic regression.
) Frequencies: chapter overview.
) Binomial test.
) Chi-squared goodness-of-fit.
) Chi-squared test of association.
) McNemar test.
) Log-linear regression.
) Factor: chapter overview.
) Reliability analysis.
) Principal component analysis.
) Exploratory factor analysis.
) Confirmatory factor analysis.
) Next steps.