r script

Proteins are linear polymers formed by 20 different amino acids and oils are composed of fatty acids. Considering Drs. Kassem and Yuan's data for protein and oil with their corresponding contents of amino acids and fatty acids, respectively (in an excel file of BIOL400 mutant_your dataset): 1. Does protein/oil content have a significant effect on the contents of amino acids/fatty acids? Explain your result (10 points). 2. Are the residuals of the variables from the analysis reasonably normal and homoscedastic? Explain your result (10 points). 3. Calculate mean, CV, variance, standard deviation, range, and standard error for all variables (10 points) 4. Create boxplots and histograms to visualize the numerical variables that you work with (5 points). 5. Create a scatterplot for the correlation on all variables (5 points). 6. Create a heatmap using your dataset and explain your result (10points) 7. Draw Q-Q plots to show the correlation between a given sample and the theoretical normal distribution on protein and oil, respectively (5 points). 8. Find Pearson's correlation coefficient between protein and oil and interpret your results (5 bonus points); 9. Create histogram on each variable with a normal curve in your dataset (5 points). 10. Conduct two-way ANOVA analysis; present an ANOVA table for the variables that you have analyzed and explain your results (10 points) 1 1. Conduct a t-test on each variable in your dataset (2016 vs 2017) and present the results and show 95% confidence interval? (10 points). 12. Perform a PCA analysis using your dataset and interpret your results (10 points). 13. Attach the command lines that have been used in the exam (10 points) The datasets for the exam have been saved as BIOL400 mutant_your name in Canvas. Fatty acids: Palmitic, Oleic, Linoleic, and Linolenic Amino acids: Asp, Threr, Glu, Pro, Gly If you have the data on fatty acids, you don't need to answer the questions related with amino acids and vice versa. Screen print will not be accepted.\f