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    Solving Biological Problems With R

    Posted By: ELK1nG
    Solving Biological Problems With R

    Solving Biological Problems With R
    Published 1/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 551.88 MB | Duration: 1h 12m

    Summarizing Data

    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