The introduction "introduces" the investigation to your reader.
It needs to:
state the issue being investigated (with justification using research).
state the relationship this issue has with the selected variable in the given data.
state the specific periods that the investigation is going to provide forecasts for.
The introduction should end in a very specific purpose statement.
Use artificial intelligence like ChatGPT to find links between a variable in the dataset and real world issues.
For example:
Be specific and find a NZ issue that is linked to the variable.
For example:
Search for specific news items that discuss the issue you have identified above:
For example:
What variable are you using?
Name the variable in the given dataset and ...
Describe how you are you going to use it to help you predict what will happen with your issue in the future?
i.e How is the variable in the dataset linked to the issue you have identified?
I am going to forecast the values of [variable in dataset] over the period [start date - end date] using the [given dataset].
I will use my forecasts of [variable in dataset] to make predictions for [the variable in my (real world) problem].
I am going to forecast the values of Arctic Sea Ice over the period January 2024- December 2025 using the Sea Ice dataset collected by NASA.
I will use my forecasts of Arctic Sea Ice to make predictions for likely changes in extreme weather events in NZ.
Your ISSUE is your CONTEXT.
It is the reason why you are doing this investigation.
You are trying to answer a question about a real issue, using a related variable in the dataset you are given.
In the first part of your report (introduction) you will need to explain how the selected variable in the dataset is related to your issue.
In the last part of your report (conclusion) you will need to describe what the forecasts for the dataset variable mean for the issue you are investigating.
Take the time to brainstorm your issue. This will help clarify the link between the variable in the given dataset and the variable in your issue.
Establishing a reason for analysing the time series of a variable in the given dataset, justifies doing the analysis.
An unjustified purpose is unlikely to gain a grade higher than 'Achieved'.
What issue are you investigating?
Why are you investigating this issue?
Who will be interested in your findings?
The data is the surface area of sea ice in millions of square kilometres.
The data is sourced from the National Snow and Ice Data Center.
Introduction
The sea ice in the Arctic plays an important part in regulating the Earth's overall temperature. By reflecting back the energy from the Sun, the ice helps to lower the overall temperature of the Earth. If this ice was to disappear, the Earth would end up reflecting less of the Sun's energy back and hence would warm up the planet. This would in turn cause land ice to melt and would raise the overall sea level.
People who live in low lying areas are concerned about the rise of sea levels as they are worried about their homes flooding. “Even a modest rise in sea levels could cause flooding problems for low-lying coastal areas.”1
Purpose Statement
I am going to forecast the amount of sea ice in the Arctic over the period Jan 2018 - Dec 2019 using the National Snow and Ice Centre Dataset. I will use my forecasts for Arctic sea ice to make an inference about sea levels in the Pacific Ocean and its effects on the flooding of coastal areas in Pacific Islands.
1. http://science.howstuffworks.com/environmental/green-science/global-warming4.htm