Questions
Part A
Old Faithful Geyser in Yellowstone National Park, Wyoming is famous for the consistency and beauty of its eruptions. The collected measurements are the duration of the current eruption in minutes (`eruptions`) and the subsequent waiting time until the next eruption in minutes (`waiting`).
Import/load the data set faithful.
Question 1: Construct an appropriate plot that displays the relationship between duration time (the explanatory variable) and waiting time (the response variable). Which of the following is the appropriate graphical display?
Question 2: Implement a Pearson Correlation test to determine whether there is a significant linear relationship between these variables. What is the correlation coefficient and appropriate conclusion to test the relationship between eruption time and wait time?
Question 3: Find the least squares regression equation (that is, the equation for the line of best fit) for this data. State the least squares regression line.
Question 4: According to the least squares regression, is there a significant association between eruption length and wait time?
Question 5: What is the appropriate interpretation of the intercept term in the least squares regression equation?
Question 6: What is the appropriate interpretation of the slope term in the equation?
Question 7: What is the predicted mean wait time when the eruption duration is 2.1 minutes?
Part B
This data set contains information about various car models. The variables that will be utilized are the price of a mid-range model (price) in thousands of dollars and the miles per gallon the vehicle reaches on the highway (mpghighway).
Import/load carprice data.
Question 8: Construct an appropriate plot that displays the relationship between average miles per gallon on the highway (explanatory variable) and the price (response variable). Which of the following is the appropriate graphical display?
Question 9: Implement a Pearson Correlation test to determine whether there is a significant linear relationship between these variables. What is the correlation coefficient and appropriate conclusion to test the relationship between mpg highway and price?
Question 10: Find the least squares regression equation for these variables. State the least squares regression equation.
Question 11: According to the least squares regression, is there a significant association?
Question 12: What is the appropriate interpretation of the slope term in the least squares regression equation?