Subject ▸ Statistics

An introduction to R for Agricultural Research

9 May 2018

Introduction Regression Analysis Simple Linear Regression Example Example Example Multiple Linear Regression Example Polynomial Regression Analysis Example Analysis of Variance (ANOVA) Example Example Analysis of Covariance (ANCOVA) Example Same intercepts but different slopes Different intercepts and different slopes Correlation Analysis Simple Correlation Analysis Example Partial Correlation Analysis Example Multiple Correlation Analysis Example Completely Randomized Design (CRD) Example Randomized Complete Block Design (RCBD) Example Latin Square Design Example Introduction R is a free, open-source programming language and software environment for statistical computing, bioinformatics, visualization and general computing.

VetResearchLMM v1.0.0 on CRAN

23 April 2018

Statistics, R, Linear Mixed Models, Veterinary Research

The latest version of the VetResearchLMM package for R is now on CRAN. This package provides R Codes and Datasets for Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998). Linear Mixed Models. An Introduction with applications in Veterinary Research. International Livestock Research Institute. The latest version of the package is prepare for new version of lmerTest.

Help

20 April 2018

Statistics, R, Python, LaTeX, Research

This is not a help service for all your Statistics, R, Python and/or LaTeX questions, so please don’t post questions in the comments, or send them to me by email. If you have questions about Statistics and/or data analysis, ask for help on crossvalidated.com. If you have questions about R, ask for help on stackoverflow.com. If you have questions about Python, ask for help on stackoverflow.com. If you have questions about LaTeX, ask for help on stackoverflow.

About myaseen208

20 April 2018

Statistics, R, Python, LaTeX, Research

This is my blog site where I will put my thoughts about Statistics, R, Python, LaTeX and Research.

Data Analysis with R: Introduction of R Language

25 March 2018

R, Statistics, Research

The Workspace Data types Vectors Matrices Lists Data Frames Reading/writing data from/to files (Import/Export Data) Connecting to the database Numerical or Graphical Summaries of data. Summarize Data Bar charts and Dot charts ggplot2 package The mpg Data Frame Data Transformation Filter Rows with filter() Comparisons Logical Operators Missing Values Arrange Rows with arrange() Select Columns with select() Add New Variables with mutate() PakPC2017Tehsil Data Frame Scatter Plot dygraphs plotly datatable The Workspace The workspace is your current R working environment and includes any user-defined objects (vectors, matrices, data frames, lists, functions).