Page 181 - Data Science Algorithms in a Week

Time Series Analysis

2. We use the 12 formulas from the example, one for each month, to predict the
sales for each month in the year 2019:

sales_january = 1.279*(year+0/12) - 2557.778 - 2.401

= 1.279*(2019 + 0/12) - 2557.778 - 2.401 = 22.122

sales_february = 1.279*(2019+1/12) - 2557.778 - 1.358 = 23.272
sales_march = 1.279*(2019+2/12) - 2557.778 - 0.464 = 24.272

sales_april = 1.279*(2019+3/12) - 2557.778 - 0.608 = 24.234

sales_may = 1.279*(2019+4/12) - 2557.778 - 0.165 = 24.784

sales_june = 1.279*(2019+5/12) - 2557.778 - 0.321 = 24.735
sales_july = 1.279*(2019+6/12) - 2557.778 - 0.003 = 25.160

sales_august = 1.279*(2019+7/12) - 2557.778 - 0.322 = 24.947

sales_september = 1.279*(2019+8/12) - 2557.778 - 0.116 = 25.259
sales_october = 1.279*(2019+9/12) - 2557.778 + 0.090 = 25.572

sales_november = 1.279*(2019+10/12) - 2557.778 + 1.833 = 27.422

sales_december = 1.279*(2019+11/12) - 2557.778 + 3.552 = 29.247

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