Use the insurance data set from the fpp3 package to answer the below questions. 1. Produce a time plot of the data and describe the patterns. Identify any unusual or unexpected fluctuations in the time series. 2. Fit a regression model with Quotes as the dependent variable and a linear trend and seasonal dummies as explanatory variables. 3. Create a plot showing two lines a fitted line from the above regression and a line with actual quotes. What do you observe in this plot? 4. Create a scatter plot showing fitted v actual. Do you observe any patterns? 5. Plot the residuals against time. Do these plots reveal any autocorrelation in the model? 6. Generate box plots of the residuals for each month. Do these plots reveal any patterns in the above model? 7. Run a Ljung-Box test and interpret the results. 8. Interpret the coefficients the one associated with the trend variable and at least one associated with a seasonal variable. 9. Use your regression model to forecast the monthly Quotes for 36 months ahead. Produce prediction intervals for those forecasts. do it in R STUDIO CODE