The effect of temperature and pressure on the extrusion behavior of a metal has been investigated. Experiments were performed to determine the extrusion rate at 200 and 300C and 40 and 60 bar.
pharmacology
Description
Deliverables:
⦁ commented R code
⦁ any produced data
⦁ report in pdf format including appropriate R output (tables, plots, etc) and short
explanations
Each answer is worth 10 points.
1. Blocking is a technique that can be used to control the variability transmitted by uncontrolled nuisance factors in an experiment.
⦁ (a) True
⦁ (b) False
2. Suppose that a single-factor experiment with five levels of the treatment factor has been conducted. There are three replicates and the experiment has been conducted in blocks of 5. Write R code for this experimental design and save the resulting dataframe as a cvs file. Make sure to add comments explaining each step.
Your output should look like this (first 5 rows):
Number Block Treatment
The effect of temperature and pressure on the extrusion behavior of a metal has been investigated. Experiments were performed to determine the extrusion rate at 200 and 300C and 40 and 60 bar. Read provided extrusion.csv file into R. Make sure to encode variables BatchBlock, Temperature and Pressure as factors. Why BatchBlock variable might be useful here? Make sure you explain your findings in each step. Visualise data, label x and y coordinates as needed. Construct boxplots to investigate the effect of Temperature and Pressure on Extrusion rate.
Construct a histogram for Extrusion Rate.
⦁ Calculate mean per group of Pressure and Temperature. Draw conclusions.
⦁ Investigate an interaction effect between Temperature, Pressure and ExtrusionRate. Draw conclusions.
⦁ Fit model with interaction without accounting for blocking effect.
⦁ Include blocking effect now.
⦁ Compare both models using anova and conclude which one is more appropriate. Why?
⦁ Choose the best model and conduct model diagnostics. Plot residuals against fitted values and investigate the normality of residuals. Draw conclusions.
⦁ Upload a zip file of your data, commented R code, report in pdf format
Instruction Files
rHelp.docx
33.7 KB
