Data science and r language
Answer below questions (refer 2AR document for info)
· Which Data structures in R are the most used? Why?
· Consider the cbind() function and the rbind() function that bind a vector to a data frame as a new column or a new row. When might these functions be useful?
Answer below questions (refer 2BR document for info)
· Do you think the regression line sufficiently captures the relationship between two variables? What might you do differently?
· In the Iris slide example (2BR), how would you characterize the relationship between sepal width and sepal length?
· Did you notice the use of color in the Iris slide? Was it effective? Why or why not?
Answer below questions (refer 2CR document for info)
· Refer back to the ANOVA example on an earlier slide. What do you think? Does the difference between offer1 and offer2 make a practical difference? Should we go ahead and implement one of them?
· If yes, and the costs were US $25 for each offer 1 and US $10 for offer2, would you still make the same decision?
· In our manufacturing plant example, assuming you could check the plant for problems in the manufacturing process, how might you justify this decision financially?