Analyze and discuss all of the above critically.

A time series is a collection of monitoring precise data obtained through repeated measurements over time (Australian Bureau of Statistics, 2020). Time series analysis is examining what has occurred lastly in order to forecast what will occur in the near future. Time series have different sequence over time and being able to determine these sequences make it easier to forecast what might happen in the future to the company. The two main sequence are trend and seasonal variation.

Seasonal variation is a variable pattern over period of time depending on products or services features. Trend is a long-term motion in a constant direction. Trend can be either positive or negative depending on data. Once calculated, trends can be used as a guide to analyse historical data to make it easier to forecast future data. When forecast is made then the business can be well managed, for instance inventory management helps to decide whether a particular product should continue to be sold or not and whether the business needs further investment to assist development of company. To do time series analysis for GDEX, both seasonal variation and trend need to be calculated.

According to data obtained through three moving average shows a continuous increase in revenue data from GDEX. Although the increase is not uniform but still shows an increment. To calculate the average increase in trend per year, transferring the data into this formula:

323.62-222.344-1 = 33.76

This shows an increasing trend increase of 33.76 per year.

The data shown in the chart clearly show a linear increase of revenue. There is one year where income exceeds the flow line which are in 2018, the rest is below the trend line. The trend line cannot go beyond 2019 because the actual data for 2021 is not yet available to calculate the three moving average formula. The gap between actual data and trend line is called as seasonal variation. From the trend analysis, we can calculate the seasonal variation that happen in GDEX.

As guided by the table above, clearly shows non-uniform and inconsistent variations. However, it can be seen in terms of decreases and increases in variation for future forecasts. Based on trend data, it can be seen an increase in total revenue for each year. It can be estimated as a long-term movement in a consistent movement. Although its value changes every year, but its value is expected to follow the average value of trend calculated earlier which is 33.76. That means total revenue will increase each year by an average of 33.76.

Given by repeating three period of seasonal variation, year 2020 will be down from the trend line. For 2021, the data variation will exceed the trend line as in 2018. This is because it can be seen that the repetition of data variation in line with the trend in previous years.