R programming: # Q1 # Create a bar chart [barplot()], showing the average retail price by HDSize. # Make sure your chart has x-axis, y-axis and bar labels. # hint: use aggregate() to get the data to plot first # x-axis label -> "Hard Drive Size" # y- label ->"Average Retail Price"

# Q2 # To better compare retail prices across stores, create a boxplot chart # of retail price by store post code. # hint: store post code is x-axis

# Q3 # A ] # We want to investigate the relationship between retail prices and # customer-store distance. # Create a ggplot scatter chart in which x-axis is customer store distance # and y-axis is retail price, # and color is "navy" and transparency is 40%.

# Q4 # A ] # By modifying your code in previous question, introduce "Configuration" # variable into the plot in the Color parameter. # Hint: set color to configuration

# Q5 # A ] # By modifying your code in previous question, introduce "screen size" variable into the plot in the Size parameter. # Also, set the point size to 4.

# Q6 # A ] # Create a facet scatter plot in which x-axis is customer store distance and # y-axis is retail price and face wrap variable is battery life.

# Q7 # A ] # Create a facet scatter plot in which x-axis is customer store distance and # y-axis is retail price, color is Integrated Wireless, and # Face wrap variable is Bundled Applications.

# Q8 # A ] 5points # Create a facet plot in which x-axis is customer store distance and # y-axis is retail price, color is battery life, # size is Integrated Wireless, and alpha is 0.70. # Face wrap variable is RAM GB.

# Q9 # Usin the 6 numeric variables (customer store distance, HD size, # Processor speed, RAM GB, Retail Price and Battery Life) # plot a basic heat map by first generating a correlation matrix