Question 1: Predict future time series

Having opened a new worksheet, with the use of a time series use sum of sales with order date. Use the continuous lines visualization and answer the following questions:

• With the time series illustrated using an annual frequency, is there any visible trend? Include a visualization and comment thereon in this document.
• Changing the frequency to quarterly, are any cycles or seasonality observed? Include a visualization and comment thereon in this document.
• Continuing with the time series using a quarterly frequency, navigate to the "Analytics" tab and perform a forecast. Also, add a linear trend line to the time series. Insert the visualization into this document and comment on the trend (or regression) line's R-squared and p-value, as well as the forecasted sum of sales for the next year compared to the previous year.

Question 2: Assess prediction performance

Using the same forecasting model produced in Question 1, navigate to "describe forecast" and answer the following questions:

• Under the summary tab, what percentage contribution have seasonality and trend made to this forecast? What is the quality of this forecast, and what is the projected change of the sum of sales between Q4 in 2017 and Q4 in 2018?
• Navigating to the "Model" tab, what is the root mean square error (RMSE) for this forecast? Suppose two other forecasts have been performed using the same data, with root mean square errors of 19.2 and 18.5, respectively. Which of the three forecasts would be the one you would identify as the most reliable, and why?
• 

Sales by year 733,215 700K 609,206 600K 500K 484,247 470,533 400K 300K 200K 100K 0K 2014 2015 2016 2017 Year of Order Date The trend of sum of Sales for Order Date Year. Sales by year(quarterly) 280K 260K 240K 220K 200K 180K 160K 143,633 Sales 140K 120K 100K 80K 60K 40K 20K 0K 2014Q1 2014Q2 2014Q3 he trend of sum of Sales for Order Date Quarter. 179,628 2014Q4 68,852 2015Q1 2015Q2 2015Q3 130,260 182,297 2015Q4 2016Q1 Quarter of Order Date 136,082 2016 Q2 2016 Q3 143,787 236,099 2016 Q4 123,145 2017Q1 2017 Q2 133,764 2017Q3 280,054 196,252 2017 Q4 Sales by year forecast (quarterly) 280K 260K 240K 236,099 220K 200K 179,628 180K 160K 143,633 Sales 140K 120K 123,145 100K 80K 60K 68,852 40K 20K 0K 2014 Q2 2014 Q4 2015Q2 2015 Q4 2016 Q2 2016 Q4 Quarter of Order Date [The trend of sum of Sales (actual & forecast) for Order Date Quarter. Color shows details about Forecast indicator. 133,764 2017 Q2 196,252 233,110 2017 Q4 123,798 2018Q2 233,110 2018 Q4 Forecast indicator M Actual M Estimate