What you'll learn
Understand data types
R for everyday data analysis
Statistical tests in R
Graphics with R
Creating reproducible reports in R
Requirements
No previous programming experience needed. You will perform statistical analyses with R
Description
1: Getting started with R2: Setting up your R environment, data types and structures, loading and installing packages3:Data exploration:Reading and writing data files, looking into data, basic graphs and basic statistics4:Introduction to common packages (tidyr,dplyr, ggplot2,reshape2,ggthemes,ggpubr, RColorBrewer, psych,corrplot, Hmisc)5:Statistical tests in R:Statistical tests are applied according to the data and your questions.ANNOVA test is used to test the means of the groups.One-way ANOVATwo-way ANOVATwo-Sample t-TestChi-squared test Wilcoxon test Kruskal-Wallis test Pearson Correlation Test Spearman Correlation Test Kendall Correlation TestFriedman TestMann-Whitney U Test6:Graphics with R:hist() function used to create Histograms.boxplot() function for creating Boxplots.Pie charts can be created by using a simple function pie() stripchart() function can be used for Strip charts.barplot() function used for Bar plots in R.7:Creating reproducible reports in RThis is very important for R code integration and reports. We want to share our reports with Classfellows, collaborators or instructors.Then, the R Markdown file can help us to recognise and compile the basic components of reports.Create the R Markdown file to submit your results in PDF, Word, or HTML using Knit.
Overview
Section 1: Introduction
Lecture 1 Introduction to R statistical Software
Lecture 2 Quick R
Section 2: Data types
Lecture 3 Data types and Descriptive statistics
Lecture 4 Statistical test in R
Lecture 5 Practice Data types and statistics
Lecture 6 Practice lecturer
Section 3: Graphics with R
Lecture 7 Graphics with R
Lecture 8 Practice Graphs
Lecture 9 practice ggplot2
Section 4: Creating reproducible reports in R
Lecture 10 R Markdown file
Beginners in programming from many field

Homepage

https://www.udemy.com/course/solving-biological-problems-with-r/

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