Data Analysis in R

See Video   ⮞  ☝ AGRON stats November 29, 2020 Introduction Importing data Visualize data Verify the structure of data Correlation analysis Using agricolae package Using stats package Getting correlation matrix Properties Limitations Introduction Every individual element in any population is composed of several quantitative as well as qualitative characters. None of the characters vary in isolation rather these are related with each other. If we study two variables at a time, the association is called bivariate . When we study many number of variables at a time, the association is called multivariate . The associationship between the variables can be linear or nonlinear . In linear association one can find three different types of relationships. Positive association between the variables Negative association between the variables No associa

See Video   ⮞  ☝ AGRON Stats August 03, 2020 In this post, you will learn how to import data, fit analysis of variance model, make comparison of treatments using LSD test and finally visualizing data by plotting bar graphs with standard error bars and placing alphabets from mean LSD test on top of error bars.  Introduction Importing data file Fit analysis of variance model LSD mean comparison test Original order of groups (for lettering) Visualizing effects Plotting genotypes Plotting gender Plotting interaction Introduction You will learn how to visualize bar graph for main and interaction effects using R studio. I shall use two way analysis of variance technique to fit a model for the given data set. Least significant difference test will be applied for mean comparisons. Bar graphs will be plotted using the alphabets from group component of LSD test to place just above the error