Learn Jamai Didactic Course in online With Scratch Examples

About the Course:

Learn jamai in this full tutorial course. jamovi is a free, open-source application that makes data analysis easy and intuitive. jamai menus and commands are designed to simplify the transition from programs like SPSS but, under the hood, jamai 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 jamai to refine, analyze, and visualize your data to get critical insights.


Course Timings:

  •  (0:00:00) Welcome
  •  (0:01:26) Installing jamovi
  •  (0:02:00) Navigating jamovi
  •  (0:05:43) Sample data
  •  (0:08:54) Sharing files
  •  (0:10:26) Sharing with OSF.io
  •  (0:13:54) jamovi modules
  •  (0:18:05) The jmv package for R
  • WRANGLING DATA
  • (0:23:07) Wrangling data: chapter overview
  •  (0:24:36) Entering data
  •  (0:26:52) Importing data
  •  (0:31:43) Variable types & labels
  •  (0:37:52) Computing means
  •  (0:41:47) Computing z-scores
  •  (0:43:43) Transforming scores to categories
  •  (0:47:25) Filtering cases
  • EXPLORATION
  •  (0:55:51) Exploration: chapter overview
  •  (0:56:56) Descriptive statistics
  •  (1:02:22) Histograms
  •  (1:06:47) Density plots
  •  (1:10:10) Box plots
  •  (1:13:35) Violin plots
  •  (1:16:13) Dot plots
  •  (1:19:20) Bar plots
  •  (1:23:08) Exporting tables & plots
  • T-TESTS
  •  (1:24:28) t-tests: chapter overview
  •  (1:33:24) Independent-samples t-test
  •  (1:40:03) Paired-samples t-test
  •  (1:45:16) One-sample t-test
  • ANOVA
  •  (1:52:23) ANOVA: chapter overview
  •  (1:54:20) ANOVA
  •  (2:06:31) Repeated-measures ANOVA
  •  (2:16:21) ANCOVA
  •  (2:30:14) MANCOVA
  •  (2:37:26) Kruskal-Wallis test
  •  (2:43:26) Friedman test
  • REGRESSION
  •  (2:48:55) Regression: chapter overview
  •  (2:51:03) Correlation matrix
  •  (2:58:34) Linear regression
  •  (3:13:36) Variable entry
  •  (3:20:51) Regression diagnostics
  •  (3:27:11) Binomial logistic regression
  •  (3:36:12) Multinomial logistic regression
  •  (3:45:03) Ordinal logistic regression
  • FREQUENCIES
  •  (3:53:28) Frequencies: chapter overview
  •  (3:55:47) Binomial test
  •  (4:00:39) Chi-squared goodness-of-fit
  •  (4:07:06) Chi-squared test of association
  •  (4:12:26) McNemar test
  •  (4:17:19) Log-linear regression
  • FACTOR
  •  (4:23:05) Factor: chapter overview
  • (4:24:54) Reliability analysis
  •  (4:32:20) Principal component analysis
  •  (4:40:18) Exploratory factor analysis
  •  (4:43:49) Confirmatory factor analysis

  • CONCLUSION
  •  (4:52:42) Next steps

Copyrights: Freecodecamp.org


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