Modeling With ANCOVA – Part 1: Exercises

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In the previous exercise on the #REcology series, we learned how to define the impact of one explanatory variable to another response variable. In a real practice, particularly in experimental or observational design, explanatory variables are often found to be more than one. Thus, it needs a new determination to analyze the data-set and generate the correct conclusion. In this exercise, we will try to do an analysis of the co-variance (ANCOVA) method. Covariates here refers to the continuous explanatory variables. It involves a combination of regression and analysis of variance. ANCOVA requires a continuous response variable, at least one continuous explanatory, and at least one explanatory factor variable. Answers to these exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page. Data-set on this exercise can be downloaded here.

Exercise 1
Load the data-set and required package, car.

Exercise 2
Do some plotting; what can be inferred? Create a basic verbal hypothesis.

Exercise 3
Create an interaction model based on the basic verbal hypothesis generated on Exercise 2.

Exercise 4
Check the interaction between the explanatory variables of the model created using ANOVA. Make sure that the interaction of those two variables is insignificant.

Exercise 5
Check the statistic summary of the model. Pay attention to the intercept, slope, and the R square of the model.

Exercise 6
Create a linear regression plot and determine the equation based on the statistic summary.

Related exercise sets:

Spatial Data Analysis: Introduction to Raster Processing (Part 1) Spatial Data Analysis: Introduction to Raster Processing: Part-3 Big Data Manipulation in R Exercises Data Manipulation with data.table (part -2) Density-Based Clustering Exercises