In R please provide the code and explanation for the following One Way ANOVA with the coagulation data set a. Load the coagulation data set (it is from the faraway library) b. Data Summaries & Assumption Check i. Use the names() function to identify the column names ii. How many rows of data are there? iii. Create a single graph with 4 boxplots on the same scale, one for the coagulation for each of the diets. Each boxplot should be a different color. Use the plot function for this task. colNameData is the name of the column in the data set that you want to create a boxplot for colNameCategory is the name of the column that you want to use to split the data into groups (so you want one boxplot for each category/value in this column)dataset is the name of the full dataset col=2:4 will give you 3 different colors (color indices are 1-8, then they repeat)
In R please provide the code and explanation for the following
One Way ANOVA with the coagulation data set
a. Load the coagulation data set (it is from the faraway library)
b. Data Summaries & Assumption Check
i. Use the names() function to identify the column names
ii. How many rows of data are there?
iii. Create a single graph with 4 boxplots on the same scale, one for the coagulation for each of the diets. Each boxplot should be a different color. Use the plot function for this task.
colNameData is the name of the column in the data set that you want to create a boxplot for
colNameCategory is the name of the column that you want to use to split the data into groups (so you want one boxplot for each category/value in this column)dataset is the name of the full dataset col=2:4 will give you 3 different colors (color indices are 1-8, then they repeat)
iv. Create 4 different data frames, one for the data corresponding to each of the 4
factors. How many observations are there for each diet?
v. Check the normality assumption for each subset by creating qq plots. Make
sure each plot has an appropriate title.
vi. What is the sample variance for each diet? Do you think that the assumption of
common variance holds? Why or why not? How could you formally test this?
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