Subject ▸ Research

Statistics: The Art & Science of Learning from Data

1 Introduction 1.1 Statistics 1.2 Variable 1.3 Measurement 1.4 Measurement Scales 2 Exploring Data with Graphs & Numerical Summaries 2.1 Graphs 2.2 Numerical Summaries 3 Descriptive Statistics 4 Correlation Analysis 5 An Introduction to Linear Models 5.1 Regression Analysis 5.2 Analysis of Variance (ANOVA) 5.3 Analysis of Covariance (ANCOVA) 6 An Introduction to R addClassKlippyTo("pre.r, pre.python"); addKlippy('left', 'top', 'auto', '1', 'Copy code', 'Copied!

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Design & Analysis of Field Experiments using R

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 Factorial Experiment under RCBD Stability Analysis Individual Analysis of Variance for each Location Combined Analysis of Variance Additive Main Effects and Multiplicative Interaction (AMMI) Analysis Additive Main Effects and Multiplicative Interaction (AMMI) Biplot Analysis Genotype plus Genotypes by Environment (GGE) Interaction Biplot Analysis Introduction R is a free, open-source programming language and software environment for statistical computing, bioinformatics, visualization and general computing.

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Training Course on Capacity Building of NARS Scientists in Advance Analytical Techniques

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 Factorial Experiment under RCBD Stability Analysis Individual Analysis of Variance for each Location Combined Analysis of Variance Additive Main Effects and Multiplicative Interaction (AMMI) Analysis Additive Main Effects and Multiplicative Interaction (AMMI) Biplot Analysis Genotype plus Genotypes by Environment (GGE) Interaction Biplot Analysis Introduction R is a free, open-source programming language and software environment for statistical computing, bioinformatics, visualization and general computing.

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An Introduction to Statistics using SPSS

Introduction Statistics Variable Measurement Measurement Scales Descriptive Statistics Example Reference Boxwhisker Diagram Example Reference Scatter Plot Example Reference Regression Analysis Simple Linear Regression Example Reference Multiple Linear Regression Example Reference Polynomial Regression Analysis Example Reference Analysis of Variance (ANOVA) Example Reference Example Reference Analysis of Covariance (ANCOVA) Example Reference Same Slopes but different Intercepts Different Intercepts and different Slopes Factorial Experiments Example Reference Introduction alt text

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Emerging Technologies in Research: Google Apps and SPSS

Introduction Statistics Variable Measurement Measurement Scales Descriptive Statistics Example Boxwhisker Diagram Example Regression Analysis Simple Linear Regression Example Exercise Exercise Multiple Linear Regression Example Polynomial Regression Analysis Example Analysis of Variance (ANOVA) Example Exercise 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 alt text

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An introduction to R for Agricultural Research

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.

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Help

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.

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About myaseen208

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

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).

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