Jamovi

Course Description

jamovi is a free, open-source application that makes data analysis easy and intuitive. jamovi menus and commands are designed to simplify the transition from programs like SPSS but, under the hood, jamovi is based on the powerful statistical programming language R. jamovi has a clean, human-friendly design that facilitates insight into your data and makes it easy to share your work with others. In this introductory course, you'll learn how you can use jamovi to refine, analyze, and visualize your data to get critical insights.

Course Information

  • Introductory level
  • 53 streaming video tutorials
  • 4 hours 25 minutes of instruction
  • Created by Barton Poulson
  • Published 29 July 2018 
  • Videos are shared freely with a Creative Commons Attribution license
  • Download the free course files here or preview them on OSF.io here

JAM01_Titles 1 01.png

Note. To navigate the videos, click on the menu icon (☰) in the top left of the video.

Table of Contents

GETTING STARTED

  • Welcome {4:57}
  • Downloads {5:43}
  • Installing jamovi {3:39}
  • Navigating jamovi {4:12}
  • Sample data {3:52}
  • Sharing files {1:54}
  • Sharing with OSF.io {3:39}
  • jamovi modules {4:57}
  • The jmv package for R {5:43}

WRANGLING DATA

  • Wrangling data overview {1:47}
  • Entering data {2:18}
  • Importing data {5:43}
  • Variable types & labels {8:00}
  • Computing variables {8:18}
  • Filtering rows {8:38}

EXPLORATION

  • Exploration overview {1:30}
  • Descriptive statistics {6:14}
  • Histograms {5:25}
  • Density plots {3:58}
  • Box plots {3:59}
  • Violin plots {2:58}
  • Dot plots {3:33}
  • Bar plots {3:51}
  • Exporting tables & plots {6:28}

T-TESTS

  • t-tests overview {5:25}
  • Independent-samples t-test {3:58}
  • Paired-samples t-test {3:59}
  • One-sample t-test {2:58}

ANOVA

  • ANOVA overview {1:30}
  • ANOVA {6:14}
  • Repeated-measures ANOVA {5:25}
  • ANCOVA {3:58}
  • MANCOVA {3:59}
  • Kruskal-Wallis test {2:58}
  • Friedman test {3:33}

REGRESSION

  • Regression overview {2:18}
  • Correlation matrix {5:43}
  • Linear regression {8:00}
  • Binary logistic regression {8:18}
  • Multinomial logistic regression {8:38}

FREQUENCIES

  • Frequencies overview {5:25}
  • Binomial test {3:58}
  • Chi-squared Goodness-of-fit {3:59}
  • Chi-squared test of association {2:58}
  • McNemar test {3:33}
  • Log-linear regression {3:51}

FACTOR

  • Factor overview {5:25}
  • Reliability analysis {3:58}
  • Principal component analysis {3:59}
  • Exploratory factor analysis {2:58}
  • Confirmatory factor analysis {3:33}

CONCLUSION

  • Conclusion {5:43}
  • Next steps {8:00}