Large Data Set

Exam Strategies: How to Analyze Large Data Sets

When taking exams, you may come across questions that require you to analyze large data sets. To ace these questions, it is crucial to familiarize yourself with the data beforehand. Exam questions typically provide partial data sets for calculation purposes.

Different Variables to Analyze in Large Data Sets

Each exam board has its own specific data set, covering a wide range of topics. For example, the Edexcel exam board focuses on weather data from various locations in the UK and other countries. This allows for the examination of different variables, such as:

• Daily Mean Temperature - measured in degrees Celsius, this is the average temperature over a 24-hour period.
• Daily Total Rainfall - any rainfall under 0.05mm is recorded as "tr" or "trace".
• Daily Total Sunshine - measured to the nearest tenth of an hour.
• Daily Mean Wind - an average over 24 hours, measured in knots or using the Beaufort scale.

Pro Tip: 1 knot is equal to 1.15 mph.

• Daily Maximum Gust - highest recorded wind speed, measured in knots.
• Daily Maximum Relative Humidity - shown as a percentage, values above 95% may indicate mist and fog.
• Daily Mean Cloud Cover - measured in octas, a unit used specifically for cloud coverage.

Pro Tip: Oktas has an 8-point scale with 0 Oktas representing a clear sky, and ⅛ Oktas meaning one-eighth of the sky is covered by clouds.

• Daily Mean Visibility - measured in decametres (Dm).
• Daily Mean Pressure - measured in hectopascals (hPa).

It is possible for the data set to have missing values, which may be indicated as "n/a" or "not available".

Sample Questions from Data Sets for Practice

Let's take a look at an extract from a large data set and explore the type of questions you may face.

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