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Jamovi – data analysis and report generation principles with elements of the R language

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Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

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Confident use of Jamovi - You will learn Jamovi's layout, modules, and key settings, so you can start working with data on your own and find the right analytical tools much faster.

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Well-prepared datasets - You will practice entering, importing, organizing data, and creating computed variables, so you can prepare a clean dataset for analysis without confusion or avoidable errors.

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Clear statistics and charts - You will create descriptive statistics, histograms, density plots, and scatterplots, helping you quickly inspect distributions and interpret patterns in your data more accurately.

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Choosing the right tests - You will work with tests for independent samples, paired samples, and one-sample designs, so you can match the method to the research question and avoid weak conclusions.

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Relationships and prediction - You will build correlation matrices as well as linear and logistic regression models, allowing you to examine relationships between variables and make stronger predictions.

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Comparing groups reliably - You will learn ANOVA, selected covariance analyses, and nonparametric tests, so you can compare groups reliably even when your data do not meet standard assumptions.

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Exploring measurement structure - You will learn how to assess scale reliability, run principal component analysis, and perform exploratory factor analysis to better evaluate the quality of measurement tools.

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Saving and sharing results - You will learn how to save datasets and outputs, archive your work, and prepare analyses for publication or sharing with others, making future work and teamwork much easier.

Training programme

1. Jamovi Software

  • Jamovi – package properties,
  • sample data,
  • Jamovi modules.

2. Installation and work with the package

  • installation of the package,
  • interface,
  • data entry,
  • data importing,
  • calculating variables.

3. Main software functions

  • descriptive statistics,
  • histograms,
  • density plots,
  • scatter plots.

4. Tests

  • tests for independent samples,
  • tests for paired samples,
  • tests for one sample.

5. Regression

  • correlation matrix,
  • linear regression,
  • binomial logistic regression,
  • multinomial logistic regression.

6. Anova

  • one-way analysis of variance,
  • multivariate analysis of covariance,
  • Kruskal – Wallis test,
  • Friedman test.

7. Factor analysis

  • reliability analysis,
  • principal component analysis,
  • exploratory factor analysis.

8. Data editing and program personalization

  • methods of data saving,
  • saving analyses,
  • personal program settings.

9. Information archiving

10. Data sharing

  • preparation and publication of one's own analyses. 

11. Summary of acquired knowledge

What are the prerequisites for participating in the training?

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Basic statistics - You should understand core statistical terms such as variable, mean, median, and correlation, so you can follow the analysis process and interpret results in Jamovi.

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Working with data - You should be comfortable using data tables and distinguishing variable types, because during the course you will import data, organize it, and create new variables.

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Computer skills - You should be able to use a computer confidently, install software, and save files, so you can complete the Jamovi setup and work through the exercises on your own.

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Reading outputs - You should be ready to work with numerical results and charts, because the training includes interpreting outputs from tests, regression models, and group comparisons.