* Note : You need to quantify the variable value of the demand . Choose suitable variable that later can give you a workable associative forecasting model , which you need to conduct in Assignment 2 .the data for assignment 2 should be used based on data taken from assignment 1

Assignment 1 -Time series forecasting You are the owner of a XYZ company in Malaysia (or in your own country). You have a loyal client and your product/service is positioned well in the market. You also have the demand data for the last 5 to 10 years of your product/service. You are required to use the previous demand data (year before 2021) and a spreadsheet program to forecast the demand in December 2021. You are required to apply each of the following techniques: Moving average Exponential trend - Linear trend Comment on the strength of each approach in terms of statistical measures such as the r2, F- test, t-test, etc. Which model and forecast do you think is best? Assignment 2 - Associative forecasting model Develop an associative forecasting model using the data of two variables that you think will have some kind of a relationship, but it is not too obvious. Use the variable that you have selected in the first part and also, it will be used to predict the other variable. Use the best approach that you obtained in Phase 1 time series data analysis) for cach of the variables. then try to match them according to the corresponding time, as shown below: Time Time series variable A (from one source) Quantifiable values of (year/month/week/day) variable A 1 2 A2 10 A10 Time series variable B (from a different source) Time Quantifiable values of (ycar/month/week/day) variable B 1 BI 2 B2 10 BIO Associative Forecasting A vs B Quantifiable values of Quantifiable values of variable A variable B BI A2 B2 A10 B10 From your associative forecasting model determine the following: (a) What is the value of the coefficient of correlation? Does it appear to indicate a high degree of association between the two variables? (b) What is the value of r? What is its interpretation? (e) Do you think this is a good forecasting model? Explain