Author: Paul Clarke
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Forecasting New Car Sales Seasonal Volume – Part 2
Where we left off with Part 1 of This Blog we examined the seasonal data as a whole and utilised this data through an ARIMA model to predict the 2018 results. For the calendar year to date, we had an accuracy of 3.88%. While that accuracy is pretty good if you were to use this method to…
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Forecasting New Car Sales Seasonal Volume – Part 1
Seasonal data analysis in Python involves examining available data of past sales in an effort to draw a forecast of what future sales are likely to be, this can be vital for many reasons such as knowing how much inventory to have on hand as well as arranging marketing activities around this. The methods in…
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Personal Introduction
I’ve long been excited by innovation and data in the workplace. After a career in hospitality working in fast food and hotels, I have found my calling in data. Currently studying Bachelor of Business majoring in Business Analytics at the University of New England I took an Introduction to Python unit where I discovered the…