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MAT005 Coursework 2021

（2019年1月至2019年5月）。

•数据可在“学习中心”中找到（20 / 21-MAT005时间序列和预测下的

••“数据”工作表列出了呼叫的日期，时间以及进行呼叫的城市

2019年1月和2019年5月31日。
••使用数据预测第1次之间的通话数量和方式
2019年6月– 2019年6月7日。如果

•他们希望以A3海报的形式与同事共享。

•对数据进行初步分析，包括两者

•检查时间序列的组成部分：

•研究选择的时间序列模型以查看

•基准和简单方法，包括：天真，

•复杂的方法，包括：SES，Holt Linear，Holt

•请记住包括适当的错误统计信息

The providers of ambulance services in
Jakarta want to understand the likely
future demand for ambulance services
in the city.
They have provided 5 months of data
(January to May 2019).
What forecasts are they interested in?
• The data is available on Learning Central (20/21-MAT005 Time Series and Forecasting under the
Assessment section) within an Excel spreadsheet called TimeSeriesCourseworkData20_21.xls.
• •The Data worksheet lists the date, time of call and the city municipality from which the call
originated. The data covers the time period between 1st
January 2019 and 31stMay 2019.
• •Use the data to predict the number and pattern of calls between 1st
June 2019 – 7th June 2019. If
you are able to accurately predict further then please do.
• They would like this in the form of an A3 poster they can share with their colleagues.
What do you need to do in your analysis
• A preliminary analysis of the data including both
numerical and graphical summaries.
• Examine the components of the time series: the
underlying trend, seasonality and error and produce
a decomposition plot.
• Investigate a selection of time series models to see
which model provides a good fit to the observed
data.
• Baseline & simple approaches, including: Naïve,
Mean, Moving Average, Simple Linear Regression.
• Complex approaches including: SES, Holt Linear, Holt
Winters, Multiple Linear Regression, ARIMAs.
• Remember to include the appropriate error statistics
and graphical comparisons for each forecasting
model.

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