Course GitHub site: https://github.com/MSCI-599
Unit 3 GitHub repository: https://github.com/MSCI-599/unit_3_penguins
This unit will cover data manipulation and visualization using the Tidyverse suite of packages in R. We'll also explore basic statistical analyses like t-tests, correlations and linear models.
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HW_3a_t-tests - Assigned: 2/24/2021, Due: 3/10/2021
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HW_3b_penguin_taxidermy - Assigned: 3/3/2021, Due: 3/10/2021
(HW_3_penguins is HW_3a and HW_3b combined in the same repo called HW_3_penguins)
New functions: install.packages(), library(), as.data.frame(), filter(), arrange(), select(), rename(), mutate(), summarize(), group_by(), ungroup(), distinct(), print(), unlist(), write_csv()
New functions: find(), ggplot(), geom_point(), geom_smooth(), geom_line(), geom_histogram(), geom_boxplot(), geom_jitter(), geom_bar(), facet_wrap(), coord_flip(), scale_fill_manual(), xlab(), ylab(), ggtitle(), ggsave(), colors(), theme_bw()
New functions: identify_outliers(), stat_qq(), t.test(), t_test(), kable(), cohens_d(), droplevels(), levene_test()
New functions: cor(), cor.test(), GGally::ggpairs()
New functions: lm(), geom_smooth(), geom_ribbon(), plot.lm(), coef(), anova(), broom::tidy(), predict(), ggPredict(), expand.grid(), expand(), broom::augment(), AIC(), step(), vif()
Inspiration, resources and material for this unit were pulled from many places, including:
Allison Horst's teaching materials and art work: https://allisonhorst.github.io/ https://github.com/allisonhorst/stats-illustrations
Data Novia: https://www.datanovia.com/en/lessons/t-test-in-r/
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse! By: Chester Ismay and Albert Y. Kim https://moderndive.com/index.html